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Studies in Corpus Linguistics SCL focuses on the use of corpora throughout language study, the development of a quantitative approach to linguistics, the design and use of new tools for processing language texts, and the theoretical implications of a data-rich discipline. General Editor Elena Tognini-Bonelli Consulting Editor Wolfgang Teubert Advisory Board Michael Barlow
Graeme Kennedy
University of Auckland
Victoria University of Wellington
Robert de Beaugrande
Geoffrey Leech
Douglas Biber
University of Lancaster
North Arizona University
Anna Mauranen
Chris Butler
University of Helsinki
University of Wales, Swansea
John Sinclair
Sylviane Granger
The Tuscan Word Centre
University of Louvain
Piet van Sterkenburg
M. A. K. Halliday
Institute for Dutch Lexicology, Leiden
University of Sydney
Jan Svartvik
Susan Hunston
University of Lund
University of Birmingham
John Swales
Stig Johansson
University of Michigan
Oslo University
H-Z. Yang Jiao Tong University, Shanghai
Volume 20 English General Nouns: A corpus theoretical approach by Michaela Mahlberg
English General Nouns A corpus theoretical approach
Michaela Mahlberg University of Liverpool
John Benjamins Publishing Company Amsterdam/Philadelphia
8
TM
The paper used in this publication meets the minimum requirements of American National Standard for Information Sciences – Permanence of Paper for Printed Library Materials, ansi z39.48-1984.
Cover illustration from original painting Random Order by Lorenzo Pezzatini, Florence, 1996.
Library of Congress Cataloging-in-Publication Data Michaela Mahlberg English General Nouns : A corpus theoretical approach / Michaela Mahlberg. p. cm. (Studies in Corpus Linguistics, issn 1388–0373 ; v. 20) Includes bibliographical references and indexes. 1. English language--Noun. 2. English language--Discourse analysis. 3. Computational linguistics. PE1205.M26 2005 425/.54--dc22 isbn 90 272 2291 6 (Hb; alk. paper)
Acknowledgements Introduction Chapter 1 The attention they have been getting Introduction 5 1.1 Halliday & Hasan’s (1976) approach 5 1.2 The class of general nouns 6 1.3 The cohesive function of general nouns: Continuum and context 7 1.4 Corpus linguistic findings 9 Conclusion 10 Chapter 2 The corpus linguistic point of view Introduction 13 2.1 Electronic corpora and the study of language 13 2.2 Corpus linguistics: Theory and methodology 16 2.2.1 Corpus-based versus corpus-driven approaches 17 2.2.2 Technical possibilities and descriptive tools 18 2.3 A lexical approach to the description of English 22 2.3.1 The lexical item 23 2.3.2 The Pattern Grammar 24 2.3.3 Lexical priming 27 2.3.4 Lexis, grammar, and text: Differences in the corpus-driven approach 28 2.4 A corpus theoretical approach to general nouns 31 2.4.1 The corpus theoretical framework 31 2.4.2 Minimal assumptions for the study of general nouns 35 Conclusion 38
ix 1
5
13
English General Nouns
Chapter 3 Minimal assumptions in practice: Interpreting corpus data Introduction 41 3.1 The corpora of the present study 41 3.2 Frequency 43 3.2.1 What does the computer count? 43 3.2.2 Frequency lists and key words 45 3.2.3 Frequency and general nouns 48 3.2.4 The nouns in the corpus study 50 3.3 Context 54 3.3.1 Analysing concordance data 54 3.3.2 Dynamic categories and ad hoc labels 58 Conclusion 61 Chapter 4 Time nouns Introduction 63 4.1 Time nouns – an overview 63 4.2 Time orientation 71 4.3 Investing time 75 4.4 Evaluation and text organisation 77 4.5 The fuzziness of meaning 81 4.6 The need for local categories of description 83 Conclusion 87 Appendix 88 Chapter 5 People nouns Introduction 99 5.1 People nouns – an overview 99 5.1.1 Meanings of people nouns 100 5.1.2 The descriptive tool ‘person’ 104 5.2 man and woman 105 5.2.1 The introducing function 107 5.2.2 The characterising function 108 5.2.3 The continuity function 109 5.2.4 The meaning of a noun in its narrow context: The support function 111
41
63
99
Table of contents
5.3 men and women 115 5.4 people 119 5.5 family 123 5.6 People nouns – the group 126 Conclusion 130 Appendix 131 Chapter 6 World nouns Introduction 141 6.1 The diversity of meanings of world nouns 141 6.2 Evaluation in discourse 144 6.2.1 Language use and language functions 145 6.2.2 Approaching evaluation 146 6.2.3 Corpus linguistics and evaluation 149 6.3 Evaluative meanings of world nouns 151 6.3.1 Adjective patterns with general nouns 152 6.3.2 Evaluative patterns of world nouns 153 Conclusion 158 Chapter 7 Re-examining the minimal assumptions Introduction 161 7.1 Frequency 161 7.1.1 Meaning and paraphrase 162 7.1.2 Frequent nouns as characteristics of texts 164 7.2 General nouns and the word class noun 166 7.3 Context 168 7.3.1 Subgroups of nouns 168 7.3.2 Local textual functions of general nouns 171 7.4 What are general nouns? 172 7.4.1 Quantitative and qualitative features of general nouns 173 7.4.2 General nouns and cohesion 175 7.4.3 A corpus linguistic view on general nouns 177 Conclusion 178
141
161
English General Nouns
Chapter 8 Developing the corpus linguistic theory Introduction 179 8.1 The methodology of the corpus study 179 8.2 Even more attention is needed 181 8.2.1 Future work 181 8.2.2 Applications 184 8.3 Describing meaning in text: A flexible approach 185 8.3.1 The elusiveness of meaning 186 8.3.2 The corpus linguistic theory – where are we now? 188 8.3.3 Flexible grammar 190
Ludwig Wittgenstein says: Die Philosophie ist ein Kampf gegen die Verhexung unseres Verstandes durch die Mittel unserer Sprache.
Translated in the Oxford Dictionary of Quotations as: Philosophy is a battle against the bewitchment of our intelligence by means of language.
In the battle against the linguistic bewitchment that I at times experienced when writing this book, I was supported by the following people. I want to thank: Erich Steiner and Neal Norrick, who were the supervisors of my PhD thesis and always gave valuable advice. Jürgen Esser with whom I started my PhD studies in Bonn. Collins Publishers for permission to use the Bank of English, and Jeremy Clear for technical support. Wolfgang Teubert and the team at the University of Birmingham, where I spent several months doing research. The DAAD and the Cusanuswerk who supported me with scholarships, but even more important than the financial support was the ‘social context’ offered by the Cusanuswerk and the friends I found there. Special thanks go to Silvia Hansen-Schirra, Michael Hoey, Ramesh Krishnamurthy, Gaby Mahlberg, Joybrato Mukherjee, Heiko Schilling, John Sinclair, Mike Stubbs, and an anonymous reviewer for reading and commenting on earlier versions or parts of this book. All remaining errors are entirely my own. . . . and thanks also go to my family and friends who made sure that, in spite of any kind of battle, life was still enjoyable. Michaela Mahlberg Liverpool August 2005
Introduction
These items are often neglected in descriptions of English. . . Halliday & Hasan (1976: 274)
The items that Halliday & Hasan (1976) consider to be neglected are general nouns. In their book Cohesion in English, Halliday & Hasan (1976) deal with general nouns in the chapter on lexical cohesion, but they make it clear that it is not possible to draw a sharp line between grammatical and lexical cohesion: On the borderline between grammatical and lexical cohesion is the cohesive function of the class of GENERAL NOUN. We can speak about a borderline here because a general noun is itself a borderline case between a lexical item (member of an open set) and a grammatical item (member of a closed system). The class of general noun is a small set of nouns having generalized reference within the major noun classes, those such as ‘human noun’, ‘place noun’, ‘fact noun’ and the like. Examples are: people, person, man, woman, child, boy, girl [human] creature [non-human animate] thing, object [inanimate concrete count] stuff [inanimate concrete mass] business, affair, matter [inanimate abstract] move [action] place [place] question, idea [fact] (Halliday & Hasan 1976: 274)
Cohesion in English has become a standard work in textlinguistics. However, more than 20 years after Halliday & Hasan (1976) pointed out the importance of general nouns, Partington (1998) observes: The literature on the class of items known as general nouns is scant; it has undoubtedly not received the attention it deserves. (Partington 1998: 90)
We can imagine a number of reasons for the situation that Partington (1998) describes. One is that the elusiveness of meaning makes “the fact that general nouns are very general in meaning” (Halliday & Hasan 1976: 276) very difficult to grasp. Another reason may be the borderline status that Halliday
English General Nouns
& Hasan (1976) claim for these items, which challenges established descriptive categories. Although Halliday & Hasan (1976) do not base their claims on data from electronic corpora, they touch upon issues that are central to corpus linguistics: they question what has long been perceived as a neat separation between lexis and grammar. A corpus linguistic description of the English language stresses the context dependency of words. A unit of meaning is not necessarily the same as an orthographic word. Instead, the description of meaning has to be based on patterns in text. The co-selection that characterises the occurrence of words in samples of natural language may cut across distinctions that are made when lexis and grammar are treated separately. With the arrival of electronic corpora, new evidence has become available to study the ways in which meaning is created in texts. It is against this corpus linguistic background that the present work aims to deal with general nouns. Can evidence from corpora justify the definition of a class of general nouns? This question is highly complex, and raises fundamental points about corpus linguistic methodology and theoretical aspects of a description of English. Therefore, the focus of the present work is twofold: on the one hand, there is the question of whether there is a group of nouns that can be distinguished from other nouns on the basis of their ‘general meaning’; on the other hand, the discussion centres on issues fundamental to a corpus linguistic approach to the description of English raising questions about the descriptive tools needed to account for the new evidence provided by corpora. In the present work, corpus linguistics is seen not merely as a methodology, but as an approach to the description of English with its own theoretical framework. Halliday & Hasan’s (1976) outline initiates the discussion of general nouns, but it will become clear that a corpus theoretical approach requires its own path to discover a group of nouns that are characterised in terms of meaning. The path that is suggested is reflected in the structure of the present work. Chapter 1 gives a brief overview of the development of the concept of general nouns, starting with Halliday & Hasan (1976), before moving on to developments of their place in theory, as seen in the literature. Chapter 2 introduces the corpus theoretical framework that forms the basis of the present work. The relationship between corpus studies and theoretical claims may be characterised as corpus-based or corpus-driven. The latter approach aims to derive descriptive categories from the observation of data, whereas the former takes a more confident stance towards existing theories. The present approach is corpus-driven. However, it is clear that completely theory-free observation is impossible. It is the relationship between theory and methodology that characterises a corpus linguistic theory. The cyclical principle of minimal as-
Introduction
sumptions is introduced to enable a corpus-driven study of general nouns. Two assumptions about general nouns are put forward: general nouns are frequent nouns, and general nouns are characterised by local textual functions. Local textual functions will be defined as functions that account for the integration of lexical items in patterns of texts. Chapter 3 discusses methodological questions deriving from the minimal assumptions, thus providing the ground for the corpus study. On the basis of their frequencies, 20 nouns (or better, forms of nouns) are selected for detailed analysis: time, year, people, years, world, way, day, life, man, part, end, women, place, things, men, business, family, thing, times, woman. A first glance at this list reveals that the overlap with Halliday & Hasan’s (1976) examples is only partial and the following chapters will show that a reader who is familiar with Cohesion in English may not necessarily have expected the topics dealt with throughout the present work. Chapters 4 to 6 present the results of the corpus analysis, dividing the nouns into three main groups: ‘time nouns’, ‘people nouns’ and ‘world nouns’. The chapters are structured according to the requirements of the data. Chapter 7 brings the results of the three groups of nouns together, and discusses the relationship between the frequency and context assumptions. General nouns will be characterised both in quantitative and qualitative terms. General nouns illustrate that textual features and features of lexical items are linked. It will be argued that a corpus linguistic approach to cohesion is fundamentally lexical. After Chapter 7 has summarised the results of the corpus study, Chapter 8 starts with an assessment of the methodology of the corpus study, and points to possibilities for future work. Chapter 8 then returns to a more theoretical discussion: the main theoretical points underlying the present work are brought together, and we will look at the implications that the study of general nouns has for the development of the corpus theoretical approach. On the whole, the corpus study of the present work can be regarded as no more than a pilot study. A discussion of textual properties of lexical items requires a detailed analysis, which will inevitably put limits on the amount of data that can be processed. The study aimed to find a compromise between what is desirable and what is feasible. Even though some questions remain unanswered, and new questions are raised, the use of corpus data initiates a view on general nouns that has not been possible before. Together with the framework in which the corpus study is set, the discussion points to new ways in the corpus linguistic description of English.
Chapter 1
The attention they have been getting
Introduction The introduction raised questions about the place of general nouns in a description of English and suggested that these nouns have not been given proper attention. In the literature, the term ‘general noun’ is found in various contexts, but it is not always clear whether Halliday & Hasan’s (1976) concept is implied, or ‘general’ is simply being used as an adjective. On the other hand, there are references to phenomena that remind us of Halliday & Hasan’s (1976) description, but an explicit relation to general nouns is not established. The present chapter will give a brief overview of ways in which phenomena as they appear in the literature may be related to Halliday & Hasan’s (1976) concept. The chapter starts with an example from Halliday & Hasan (1976) that is often quoted in references to their approach. The sections that follow distinguish three types of links to Halliday & Hasan’s (1976) concept: Section 1.2 refers to linguistic descriptions that are concerned with classifications of words and overviews of linguistic categories, Section 1.3 deals with approaches that focus in more detail on functional features that are similar to those of the cohesive function, and Section 1.4 mentions two corpus studies that explicitly aim at an investigation of general nouns.
. Halliday & Hasan’s (1976) approach As pointed out in the introduction, Halliday & Hasan (1976: 274) regard general nouns as a class of nouns on the borderline between lexical and grammatical items. These nouns create a special kind of cohesion that Halliday & Hasan (1976) illustrate with the following, often-quoted, example:
English General Nouns
(1)
The ascent The climb I turned to the ascent of the peak. The task is perfectly easy. The thing It (Halliday & Hasan 1976: 279)
The example shows a continuum of cohesive elements (Halliday & Hasan 1976: 279): the first case is a repetition; then we find a synonym, which is followed by a superordinate; thing is a general noun, and finally we have the pronoun it. Thus, from top to bottom on this scale, the expression becomes more general, with the general noun thing coming just before the pronoun it. The borderline status of general nouns allows for a lexical as well as a grammatical interpretation of this situation: general nouns are “the superordinate members of major lexical sets, and therefore their cohesive use is an instance of the general principle whereby a superordinate item operates anaphorically as a kind of synonym” (Halliday & Hasan 1976: 275). From a grammatical point of view, the unit that is formed by the definite article and a general noun is similar to a pronoun.
. The class of general nouns In the literature, the borderline between open and closed classes has been questioned, for instance by Winter (1977), Bolinger (1977) and Ivaniˇc (1991). But, as in other works that deal with this problem, links to Halliday & Hasan (1976) are only implicit or play a marginal role. Winter (1977) defines a class of words in between open system and closed system words. A subgroup of this class are the ‘vocabulary 3’ items which are lexical items that resemble general nouns because of their general meaning. The functions of vocabulary 3 items, however, focus on different aspects than the cohesive function. Bolinger (1977: 50) establishes similarities between pronouns and nouns when he identifies “a sizable vocabulary of nouns more or less stereotyped as classifiers [. . .], sharing coreferential functions with pronouns”. Ivaniˇc (1991: 93) introduces ‘carrier nouns’ as a group of items “with both open- and closed-system characteristics”. In the clause, carrier nouns can take a complement; beyond the clause, carrier nouns resemble pronouns. Ivaniˇc (1991: 97) makes it clear that carrier nouns and general nouns overlap, but she sees general nouns “at the ‘fuzzy’ edge of the ‘carrier’ category”. In reference grammars, we may also identify some tentative
Chapter 1. The attention they have been getting
links to Halliday & Hasan (1976). In Quirk et al. (1985: 1442), for instance, we find ‘general hypernyms’ which have functions that are similar to the cohesive function of general nouns. Furthermore, in the Cobuild Grammar, there is a chapter that lists nouns which are “used to refer back in a general way to what has already been said” (Sinclair et al. 1990: 389f.), and we may follow Schmid (1993: 169) in taking this chapter as a description of functions of general nouns. More obviously connected to Halliday & Hasan (1976) are those texts which explicitly discuss general nouns in the context of cohesion. Martin (1992: 287), for instance, stresses that general nouns can be easily distinguished, as they are not tonic when they function cohesively. However, what he finds problematic is their role in lexical cohesion. He prefers to collapse the categories hyponymy, superordination and general item (Martin 1992: 288). The status of general nouns seems less controversial when they occur within overviews of cohesive devices, as they appear in reference works or textbooks, for instance in Lombardo et al. (1999: 29), Dirven (1989: 637f.), Salkie (1995: 18f.), Baker (1992: 183), Jackson (1982: 105). When overviews present Halliday & Hasan’s (1976) categories, they tend to use their examples, too. If they do not, the alternative examples do not always seem to be as convincing. Hatch (1992: 226), for instance, illustrates the continuum of cohesive elements with the noun runner as a general word, which intuitively feels less general than Halliday & Hasan’s (1976) examples that include nouns such as people, person, man, stuff, thing, and place. The problem of grasping the notion of ‘general meaning’ is further illustrated when Chalker (1996), in her guide to ‘linking words’, feels it necessary to distinguish between ‘general nouns’ and ‘very general nouns’ (cf. Chalker 1996: 82ff.).
. The cohesive function of general nouns: Continuum and context Focusing on the cohesive function, the meaning of general nouns can be described in comparison to other elements in a continuum of cohesive devices, as well as in relation to the preceding text to which the noun refers. In the literature on referring expressions, hierarchies of different types of referring expressions are not uncommon, cf. for instance Gundel (1989), Ariel (1988), Givón (1983). Such discussions of anaphoric noun phrases, however, tend to concentrate on grammatical aspects of the noun phrases (distinguishing, for instance, different types of determiners), whereas lexical aspects of the head of the noun phrase seem to be of marginal interest. Almor (1996) and Passonneau (1996) are two examples of approaches that distinguish between different types
English General Nouns
of anaphoric noun phrases. They draw on psycholinguistic arguments, and work with empirical data from experiments. From their concepts of ‘category terms’ and ‘basic levels’, links to general nouns may be established (cf. Mahlberg 2000). At the same time, psycholinguistic arguments raise questions about Halliday & Hasan’s (1976) continuum of cohesive elements. Halliday & Hasan’s (1976) examples seem to assume that each level of the continuum is equally acceptable. However, such lexical taxonomies can be shown to have one level, the basic level, that tends to be preferred by speakers in actual communication. Similar arguments about taxonomies are put forward in the area of lexical semantics by Cruse (1977, 1986). Further aspects of lexical taxonomies concern variation according to speaker and textual context. Tversky (1986: 67) points to the question of the basic level shifting (downwards) with the speaker’s expertise, so that, for example, “for an airplane mechanic, types of airplanes may be basic” (Tversky 1986: 67), and from a textual point of view it can be argued that we find “temporary taxonomies and ad hoc hierarchies” depending on a specific text (Cumming & Ono 1996: 94). Arguments dealing with a continuum of cohesive elements highlight features of general nouns by comparing them to other nouns that may function cohesively. Additionally, the discussion can focus on the relation between the general noun and the element in the preceding text to which the general noun refers. The interesting point about general nouns seems to be the way in which they refer back not only to previous noun phrases but also to longer stretches of texts. In Halliday & Hasan (1976) this aspect of the cohesive function, which would be a type of ‘extended’ or ‘text’ reference (cf. Halliday & Hasan 1976: 52f.), does not seem to play a central role (cf. Mahlberg 2000: 31ff.). However, possible links between general nouns and preceding stretches of text are the basis on which parallels between general nouns and other subclasses of nouns can be established, e.g. A-nouns (Francis 1986), labels (Francis 1994), shell nouns (Hunston & Francis 2000; Schmid 2000), signalling nouns (Flowerdew 2002). What these groups of nouns have in common with general nouns in cohesive function is that their meaning depends on other elements in the context. According to Francis (1994: 88), for instance, a noun that can function as a label is “unspecific and requires lexical realization in its immediate context”. An example from Francis (1994: 85) is the following, where this problem follows its lexicalisation and thus serves to “encapsulate1 or package a stretch of discourse”:
Chapter 1. The attention they have been getting
(2) . . . the patients’ immune system recognised the mouse antibodies and rejected them. This meant they did not remain in the system long enough to be fully effective. The second generation antibody now under development is an attempt to get around this problem by ‘humanising’ the mouse antibodies, using a technique developed by. . .
Distinctions and overlaps between the different subgroups of nouns, and between these groups and general nouns, can depend on the focus on cohesive relations (anaphoric only, or anaphoric and cataphoric) and/or typical structures that the nouns take within clauses (e.g. his belief that, the aim is). But differences can also lie in the functional interpretation of the occurrences of the nouns; for example they can function as textual signals indicating units of information, they may label and evaluate stretches of discourse, they may be regarded as metalinguistic nouns (e.g. advice, claim, objection), and so on. Another aspect of the cohesive function of general nouns is the possibility of vagueness (cf. Partington 1998: 91; Krenn 1985: 90). Carter & McCarthy (1997: 16) regard ‘general words’ as a subcategory of vague language. General words are normally nouns, e.g. thing, business, stuff ; they are frequently used in spoken language and “enable a speaker to express attitudes and feelings without needing to locate an exact or precise referent” (Carter & McCarthy 1997: 16).2
. Corpus linguistic findings In the overview above, we find studies that work with corpus data, in particular Francis (1986, 1994), Hunston & Francis (2000), Schmid (2000), and Flowerdew (2002); but as general nouns are only part of another group of items that is the main focus of interest, the results of these studies can only make a limited contribution to the discussion of general nouns. An exception is Partington (1998), who explicitly focuses on general nouns and discusses examples from corpora in a subsection of a chapter on cohesion (Partington 1998: 89– 96). He makes two main points: although Halliday & Hasan (1976) stress that general nouns in cohesive function tend to occur with the definite article, “a surprising number” of cohesive uses with a and such can be found (Partington 1998: 91f.): (3) Those are they who walked through the bitter valley and made it a place of spring.
English General Nouns
(4) They abandoned the felling of tropical trees to get at the plants established in their branchings, but burned a forest to ensure a monopoly in orchids. Such things hit you in the pit of the stomach.
The second point is that Halliday & Hasan’s (1976) focus on anaphoric reference seems to be too restrictive. An example of cataphoric reference is the following (Partington 1998: 92): (5) there are also things it is more difficult for parents to get a grip on, such as empathy, and the ability to retain ideas and hold them despite everybody else telling them [. . .]
Partington (1998: 92–96) supports his claims with a discussion of examples of the general noun phrase a move. Further corpus linguistic observations on general nouns are reported in Mahlberg (2000), which is a small-scale study of the nouns girl and move in the LOB corpus and in a subcorpus of the spoken part of the BNC. The results of this study suggest, for instance, that the interchangeability of general nouns and pronouns, as illustrated by Halliday & Hasan’s (1976) continuum of cohesive elements, does not hold automatically in cases of the cohesive use of general nouns. Furthermore, the point that “[a] general noun in cohesive function can in fact accept only non-defining Modifiers” (Halliday & Hasan 1976: 277) seems to require modification against the background of the results for move which illustrate how modifiers enable reference to longer stretches of text.
Conclusion The brief overview that is given in the present chapter shows that aspects of the concept suggested by Halliday & Hasan (1976) can be developed in different ways, and links to various theoretical contexts are possible. On the one hand, this illustrates the challenge that Halliday & Hasan (1976) put to linguistics when they describe a phenomenon that cuts across borderlines which typically guide the paths of linguistic discussion. On the other hand, the diversity of points of view on general nouns is evidence of the elusiveness of the object of discussion: meanings and functions are difficult to describe. The information from corpora further adds to this point: it is not only that the phenomenon is difficult to describe, we are not even aware of all of its facets. Thus, a way that seems most promising in the discussion of general nouns is a corpus linguistic approach. Corpora provide evidence of language use, so that statements about
Chapter 1. The attention they have been getting
meaning can be linked to observable features of language. Furthermore, in the attempt to identify characteristics of general nouns and to find their place in a description of English, a corpus-driven approach may focus our view: it is not theoretical arguments that determine which points deserve most attention, but corpus data.
Notes . Conte (1996: 1) uses the term ‘anaphoric encapsulation’ to refer to similar examples, she defines ‘anaphoric encapsulation’ as “a lexically based anaphora constructed with a general noun” (Conte 1996 :1). Conte’s (1996) use of the term ‘general noun’, however, is not fully clear, as she refers to Halliday & Hasan (1976) but also seems to deviate from their approach (cf. Mahlberg 2000: 29f.). . On ‘general words’ see also McCarthy (1998: 118).
Chapter 2
The corpus linguistic point of view
Introduction The aim of studying general nouns in a corpus linguistic framework is motivated by the fundamental claim that language is best described on the basis of evidence from naturally occurring language data. The present chapter starts with a brief introduction to electronic corpora and the question will be asked how corpora could be used in a discussion of the concept of general nouns. The answer to this question is not straightforward and it will be necessary to consider the role of corpus linguistics in a description of the English language. Section 2.2 will discuss basic issues that concern the relationship between theory and methodology in the study of corpora. In Section 2.3 it will be argued that corpus linguistics calls for a lexical approach to the description of English, which focuses on co-selection patterns of words in texts. A lexical approach enables a detailed description of lexical items as units of meaning, comparisons across words become possible with the Pattern Grammar approach, and the theory of lexical priming links features of words to properties of text. However, within the framework of existing approaches the practicality of a corpus linguistic investigation of general nouns still seems to be problematic. Thus Section 2.4 will outline how the present work views the question of general nouns in a corpus theoretical approach to the description of English.
. Electronic corpora and the study of language ‘Corpora’ are large collections of computer-readable texts that are used to investigate language. It seems only natural that linguists have an interest in recorded examples of language behaviour, but only the availability of computers has made it possible for linguists to profit from the potential of enormous amounts of naturally occurring text. The naturalness of texts in corpora distinguishes corpus data from empirical data (as is elicited in experiments, for
English General Nouns
instance), and computer technology enables the storage and processing of large quantities of texts. The development of corpus linguistics started in the second half of the last century. Pioneering work was done in the 1960s by Nelson Francis and Henry Kucera, who compiled the Brown Corpus, a corpus containing 1 million words of written American English printed in 1961. Together with its British English counterpart, the LOB Corpus, these were the first electronic corpora that came to be used by many linguists all over the world. As the compilation of corpora and the development of research tools often depends on financial support, corpus research has profited from co-operation with commercial partners, as in the case of dictionary making (cf. the COBUILD project, Sinclair 1987). Corpus linguistics started with a focus on the English language, but the number of projects for languages other than English is continually increasing. Furthermore, corpora can be used for comparative studies across languages. A more recent approach in corpus linguistics is the use of the world wide web as a corpus (cf. e.g. Renouf et al. 2004). Corpus research, methodology, and applications are closely related (cf. Section 2.2) and corpora are not only of use in linguistics but in a variety of fields that are concerned with language, e.g. language teaching (e.g. Johns 1991; Mukherjee 2002; Sinclair 2004a), translation studies (e.g. Hansen 2003; Olohan 2004), political sciences (e.g. Partington 2002), etc. Before linguistics could draw on innovative technologies, pre-electronic corpus work had already been conducted in various areas. Concordances and indexes were created for the Bible and works of important authors such as Shakespeare. For the Oxford English Dictionary as well as for Johnson’s Dictionary of the English Language, quotations recorded on paper slips were used as a source of illustrations for dictionary entries. In the field of language education, word frequency information was derived from corpora (e.g. Thorndike & Lorge 1944; West 1953). Descriptive grammars also made use of text collections, e.g. Jespersen (1909–1949), Poutsma (1926–1929). A transition from non-electronic corpus-based work to modern corpus linguistics is seen in the Survey of English Usage Corpus (cf. Kennedy 1998: 17). The project was started by Randolph Quirk in 1959 and the compilation of this 1 million-word corpus took about 30 years. The corpus consists of spoken and written texts, which were sampled according to pre-set criteria. All word tokens are recorded on paper slips with a specified amount of context and grammatical information; the spoken texts also contain prosodic annotations. Eventually, the corpus was computerised and the spoken part was published separately as the LondonLund Corpus.
Chapter 2. The corpus linguistic point of view
Today, corpus linguistics is “inextricably linked to the computer, which has introduced incredible speed, total accountability, accurate replicability, statistical reliability and the ability to handle huge amounts of data” (Kennedy 1998: 5). That the advantages of modern technologies in linguistics were not broadly appreciated right from the start is illustrated by an anecdote that Francis (1982) reports: In 1962, when I was in the early stages of collecting the Brown Standard Corpus of American English, I met Professor Robert Lees at a linguistic conference. In response to his query about my current interests, I said that I had a grant from the U.S. Office of Education to compile a million-word corpus of present-day American English for computer use. He looked at me in amazement and asked, ‘Why in the world are you doing that?’ I said something about finding the true facts about English grammar. I have never forgotten his reply: ‘That is a complete waste of your time and the government’s money. You are a native speaker of English, in ten minutes you can produce more illustrations of any point in English grammar than you will find in many million words of random text.’ (Francis 1982: 7f.)
This situation is symptomatic of the controversies that marked the beginning of corpus linguistics. There were those who gave priority to the native speaker’s intuition and rejected the usefulness of corpora, and there were others who took a radical empiricist approach. Fillmore (1992) caricatures these extreme positions as the ‘armchair linguist’ who only works with examples he can invent sitting in his armchair, and the ‘corpus linguist’ who is addicted to the numbers and statistics that his computer can produce. With the ongoing development of corpus research, the extreme positions gave way to a more balanced view, and it now seems widely accepted that corpora and intuition are not mutually exclusive but complement each other (e.g. McEnery & Wilson 1996: 18). Automatically retrieved data has to be interpreted by the human observer and a critical attitude is necessary to avoid a skewed picture. The strength of corpora is that they provide a basis for frequency information and they can bring to light phenomena that humans are unaware of. As Biber et al. (1998) note: In many cases, humans tend to notice unusual occurrences more than typical occurrences, and therefore conclusions based on intuition can be unreliable. (Biber et al. 1998: 3)
This situation may be reflected in dictionaries, grammars, reference works or teaching materials that are not informed by corpora. Even if they do not give wrong information they are likely to provide only part of the story. An often
English General Nouns
quoted example is the use of any. Traditional grammars state that any, in contrast to some, is used in questions and in negative or conditional contexts. Corpus findings, however, show that in roughly 50 per cent of its occurrences any is found in positive contexts, see for example Tesch (1988: 62f.), Tognini-Bonelli (2001: 17). The fact that general nouns have not attracted much interest in linguistics may also be due to such a mismatch between our intuitions and actual language use. The question is how a corpus linguistic study should proceed in order to find out whether there is any such thing as general nouns. One possibility would be to try to operationalise as many as possible of the characteristics of general nouns that Halliday & Hasan (1976) describe. We could, for instance, look at all the examples of general nouns that Halliday & Hasan (1976) list and see what percentage of their occurrences function cohesively. Furthermore we could formalise constructions in which a noun functions cohesively and see which other nouns, in addition to the Halliday & Hasan (1976) examples, we find. The search for nouns that occur in particular constructions would resemble, for instance, Schmid’s (2000) procedure for shell nouns. If we operationalise sufficient criteria our corpus data might eventually provide some yardstick – possibly with quantifiable characteristics – that could tell us whether a noun is a general noun or not. A completely different approach would be to look at all nouns in our corpus, describe the behaviour of each noun and try to find subgroups of nouns by comparison. Eventually we might or might not find a group that shows similarities to what Halliday & Hasan (1976) describe. Both approaches are problematic. What is obvious are the practical problems. Even though there are projects that work on automatic processes for tracking anaphoric relations in corpora (see e.g. Botley & McEnery 2000) it does not seem that Halliday & Hasan’s (1976) theory can yet be satisfactorily modelled. Similarly, the idea of describing all nouns in a sufficiently detailed way seems – at present – a practical impossibility. However, without going into technical details just yet, the two approaches do illustrate more fundamental considerations that may determine the way in which a corpus can be used, and that play an important role in the theoretical impact of corpus linguistics.
. Corpus linguistics: Theory and methodology It has long been a matter of discussion whether corpus linguistics is primarily a method that can be applied in a variety of fields, or whether corpus linguistics
Chapter 2. The corpus linguistic point of view
can also be a discipline in its own right with its own theoretical claims. When corpus linguistics started off, the main reaction was the excitement about various unexpected findings and technical possibilities. However, the interest in the theoretical consequences of corpus findings has been gaining importance. Section 2.2.1 will start with theoretical positions on corpus linguistics and Section 2.2.2 will go into more detail by illustrating how technical possibilities and descriptive tools may shape the investigation of language. .. Corpus-based versus corpus-driven approaches As corpus linguistics is concerned with the investigation of natural language data, it may be considered as descriptive linguistics par excellence. Jackson (1982) views descriptive linguistics in the following way: This approach starts with a language as it is spoken and written, with the data of actually occurring utterances and sentences, and seeks to analyze, catalogue and describe that data and that language. Descriptive linguistics is about describing languages rather than about constructing theories and models. It must, of course, use categories of description, but these arise inductively from a consideration of the language data rather than deductively from the axioms of a theory. (Jackson 1982: ix)
In particular the last sentence reads like an argument for equating corpus linguistics and descriptive linguistics. However, the distinction that Jackson draws between description and theory needs closer inspection. As Halliday (1994: xii) points out “ ‘facts’ are constructed by theories; there can be no such thing as a theory-free description of grammar” and we can apply this beyond grammar to language in general. Hunston & Francis (2000: 250) take Halliday’s (1994) remarks further and add “both facts and theories are, in a sense, constructed by methods”. Thus, on the one hand, it is obvious that the potential of corpus linguistics and its role in linguistics will be seriously underestimated if we regard it as a method only. On the other hand, while corpus linguistic case studies are often illustrative with regard to the short-comings of existing theories, corpus linguistics is still a long way away from the creation of a unifying theory that accommodates individual findings within a broader framework. To characterise the relationship between corpus work and linguistic theories, the terms ‘corpus-based’ and ‘corpus-driven’ have come to be used for two extreme positions. At one end we find corpus-based linguists who adopt a ‘confident’ stand with respect to the relationship between theory and data in that they bring with them models of language and description which
English General Nouns
they believe to be fundamentally adequate, they perceive and analyse the corpus through these categories and sieve the data accordingly. (Tognini Bonelli 2001: 66)
In this way corpus data can lead to modifications or adjustments of a theory and/or is used as quantitative evidence. The first of the two suggestions made above with reference to general nouns would be a corpus-based approach in the sense that Halliday & Hasan’s (1976) theory is taken as the basis for the design of a corpus study. An example of such a corpus-based approach can be found in Mahlberg (2000) (cf. Chapter 1) where possible modifications of Halliday & Hasan’s (1976) theory are discussed on the basis of corpus findings. The second suggestion made above (which aims at a comparison of the behaviour of all nouns) would be in line with a corpus-driven approach, where the aim is to “derive linguistic categories systematically from the recurrent patterns and the frequency distributions that emerge from language in context” (Tognini Bonelli 2001: 87). Within a corpus-driven approach the theoretical statements reflect the evidence that the corpus provides, and the methodological path can be described as follows: “observation leads to hypothesis leads to generalisation leads to unification in theoretical statement” (Tognini Bonelli 2001: 85). But what does this mean in practice? How far do we have to go in an attempt to let the data come first? In the search for a description of general nouns can we take for granted that we know what a noun is, or would we have to start even earlier with a description of all words before we can form classes such as nouns? .. Technical possibilities and descriptive tools While one may be easily convinced by the idea of a language description that truly reflects the language phenomena that are found in corpora, it is more difficult to see the practicality of this principle. An often quoted remark by Sinclair (1991: 100) is that “[t]he language looks rather different when you look at a lot of it at once”, but you will not be able to see anything if you do not know how to focus your view or if you wear the wrong glasses. Technical possibilities and descriptive tools are two factors that have an important impact on what we will be able to see in a corpus. Electronic corpora provide us with ever-increasing amounts of language data, but the data can only be of use because we have ways of accessing it. Thus corpus technology beyond the mere compilation of texts plays an important role. It has enabled researchers to see phenomena they had never thought about, and the revolutionary character of corpus linguistics was best
Chapter 2. The corpus linguistic point of view
revealed when the technical possibilities triggered off developments that were not intended when the researchers switched on their computers. As Sinclair (1991: 2) recalls, the Cobuild project, that set new standards in dictionarymaking, started off with modest aims and “[t]he computer was thought of as having principally a clerical role in lexicography – reducing the labour of sorting and filing and examining very large amounts of English in a short period of time”. One of the tasks that the computer is good at is counting words and providing statistical information. Thus we can observe what is typical in language, we can base descriptions of register variations on quantitative findings, and we can discover patterning in the behaviour of words, which becomes obvious through observing the recurrent combinations of those words. Technological development plays a crucial role in corpus linguistics. However, the greatest strength of technology may at the same time be a weakness if it delays certain types of discoveries and developments. An over-enthusiasm for numbers may result in the traditional syntactic canon being simply worked through and quantified; or technical innovation may result in researchers being carried away by the fascination of improving taggers, i.e. tools to add linguistic information to the words in corpora. New insights may be prevented by the distance between the data and the researchers’ perception, which may be filtered or distracted by annotation, statistics or automatic extractions of predefined phenomena. I am not saying that quantitative information and the technical support of computers are unimportant – far from it, but the usefulness of technical tools depends on the aim of the study. What is technically possible may not help to answer the question we want to investigate, and at the same time a method that would be desirable for the discussion of a linguistic problem may be prevented by technical limitations. Technology is closely related to the descriptive tools that are used in the study of corpora. Even if the aim is to follow a corpus-driven path, what is observed in the corpus needs to be named and described. Without going into a philosophical discussion of how far language shapes the world, it will be obvious that the descriptive apparatus will have an impact on the results. A corpus linguistic approach that aims to be open to new linguistic insights has to find descriptive tools that are flexible enough to accommodate what we find in the corpus. Some grammatical terminology may have to be treated with caution, as it reflects a specific attitude towards the functioning of language and has consequences for the interpretation of individual examples against the background of what is taken to be the norm. Let us take the example of ‘extraposition’, for instance. In the sentence It is obvious he is right the it is typically analysed as ‘dummy it’ that fills the space of the subject while there is an ‘extraposed’ sub-
English General Nouns
ject: he is right. Hunston & Francis (2000) pointing to results by Francis (1993), argue that examples of the supposed pretransformation type are extremely rare, and it makes a great deal more sense to accept It is obvious he is right as a pattern in its own right, and analyse it accordingly, rather than regarding it as a version of something that hardly ever occurs. (Hunston & Francis 2000: 157)
The problem of terminology also becomes obvious when we look at different ways of dealing with the relationship between lexis and grammar. Even before the existence of computer corpora, it had become obvious that the combination of words in text could not be fully described solely by syntactic rules which are applied to single words. Thus a range of terms have come to be used for phenomena that seem to be insufficiently accounted for by a grammatical analysis that treats the word as an independent unit of meaning. We find terms such as ‘lexical phrases’, ‘idioms’, ‘fixed phrases’, ‘prefabricated phrases’, ‘formulae’, ‘institutionalised collocations’, and ‘compounds’. All of these point to the fact that in some sequences of words, the words are more tightly related to each other than in other sequences, and that there is not always a one-to-one relationship between single words and meanings. The terminological variety illustrates different approaches to explaining what is left unaccounted for by syntactic rules. In the case of ‘idioms’, for instance, the semantic point of view plays an important role. ‘Idioms’ are typically identified if the meaning of the whole expression cannot be analysed as the sum of the meanings of the component parts as in it’s raining cats and dogs. There are, however, different degrees of idiomaticity and in typologies of idiomatic or lexical phrases the variability of an expression also plays a part. While expressions like by and large, or of course do not allow for variation, it is possible to say she drives me batty as well as she drives me nuts. Another way of looking at combinations of words that are not analysed in the normal syntactic way is with regard to discourse functions; ‘formulaic’ expressions, such as Many happy returns, How do you do are often associated with particular social contexts. The term ‘prefabricated phrases’ hints at the psycholinguistic point of view of language production that is relevant, for instance in language teaching (cf. Pawley & Syder 1983; Nattinger & De Carrico 1992). The contribution that corpus linguistics can make to the interface of lexis and grammar can take various forms. It has become obvious, for instance, that highly idiomatic expressions are not common, and corpus data can provide further information on the distribution of such phrases. Biber et al. (1999: 1025) show, for instance, that expressions such as how do you do, a piece
Chapter 2. The corpus linguistic point of view
of cake, a slap in the face, occur occasionally in fiction, but are rarely used in other registers. Furthermore, corpora provide evidence that variability and flexibility in the forms of idiomatic expressions have been underestimated previously (cf. Moon 1998). Although this is important information, providing a more realistic picture of language cannot by itself bring about fundamental changes in linguistic theory, as long as the terminology remains unquestioned. To talk about ‘idioms’, ‘fixed phrases’, ‘formulae’, etc. is to use some kind of ‘last resort’ categories and implies an exceptional status with regard to a system that is actually characterised by flexible combinations. In corpus linguistics the concept of ‘collocation’ may be used as a relatively neutral descriptive tool to focus on surface features of language. The term ‘collocation’ was already in use before the advent of electronic corpora to describe words in their contexts. (The term ‘collocation’ is typically associated with the work of J. R. Firth). With the help of the computer, co-occurrence can now be quantified and collocation can be defined in statistical terms: two words collocate if they co-occur more frequently than could be expected on the basis of the distribution of the individual words. Different statistical measures are used to determine significant collocation (cf. e.g. Barnbrook 1996: 92ff.), and in corpus tools a function to compute collocation measures has come to be a standard feature. It could be argued that the term ‘collocation’ is as difficult as all the others listed above, since it is used with different meanings in different frameworks, and in Chapter 3 some caution will be expressed about the use of statistics in the analysis of language. But it allows the option of focusing on surface features that can form the basis for further interpretation. While the interest in collocation often focuses on lexical words, Renouf & Sinclair (1991: 128) observe that “[c]o-occurrences in the language most commonly occur among grammatical words”. Renouf & Sinclair (1991: 128) illustrate this phenomenon by describing ‘frameworks’ which “consist of a discontinuous sequence of two words, positioned at one word remove from each other”, examples are a + ? + of, an + ? + of, be + ? + to, too + ? + to, for + ? + of, had + ? + of, many + ? + of. A different approach to the co-occurrence of words in a sequence is the ‘lexical bundle’. Biber et al. (1999: 989) regard lexical bundles as “extended collocations: bundles of words that show a statistical tendency to co-occur”, for instance do you want me to, in the case of the, the presence of a. Lexical bundles are defined on purely quantitative grounds and in most cases they do not form a structural unit (Biber et al. 1999: 990ff.). Biber et al. (1999) are mainly interested in the distribution of lexical bundles across registers, whereas Renouf & Sinclair (1991) go on to interpret the elements that are found in the middle of a frame functionally, and show that frameworks
English General Nouns
are highly selective of the words that complete the sequence. Thus the concept of collocation exemplifies how descriptive tools can reflect different theoretical directions in corpus linguistics.1 The relationship between quantitative and qualitative information from corpora will play an important role in the present study and Chapter 3 will take up the point in more detail.
. A lexical approach to the description of English Collocation can be interpreted as illustrating a fundamental point about meaning in text: combinations of words in text reflect patterns of co-selection that contribute to the creation of meaning. The co-selection of words in text is described by Sinclair (1991) with reference to the ‘idiom principle’. The idiom principle states that “a language user has available to him or her a large number of semi-preconstructed phrases that constitute single choices, even though they might appear to be analysable into segments” (Sinclair 1991: 110). The idiom principle alone does not account for all instances of language in text, but combines with the open-choice principle according to which a language text is “the result of a large number of complex choices. At each point where a unit is completed (a word, phrase, or clause), a large range of choice opens up and the only restraint is grammaticalness” (Sinclair 1991: 109). The evidence from corpora suggests that the idiom principle dominates the operating of language. However, as Sinclair (1991: 110) points out, conventional grammars tend to follow the open-choice principle. Thus, issues concerning units of language description may be raised. Sinclair’s (1998) concept of the lexical item, which is outlined in Section 2.3.1, describes the co-selection of words in complex lexical structures that form units of meaning. While Sinclair (1998) focuses on detailed accounts of individual lexical items, Hunston & Francis (2000) suggest the ‘pattern’ as a descriptive tool that can capture similarities between the behaviour of words in a Pattern Grammar (Section 2.3.2). In Section 2.3.3, it will be stressed that features of texts also have a part to play in a lexical description of English, and Hoey’s (2004a, b) theory of lexical priming will be introduced. Section 2.3.4 will compare the three approaches (Sinclair, Hunston & Francis, Hoey) with regard to the aim of a corpus-driven investigation of general nouns.
Chapter 2. The corpus linguistic point of view
.. The lexical item The work of John Sinclair stresses that meaning is not primarily linked to words but “meaning arises from words in particular combinations” (Sinclair 1998: 23). To describe units of meaning that are larger than a single word, Sinclair (1998)2 suggests the ‘lexical item’. A lexical item is a unit whose internal structure is characterised by five categories of co-selection. The invariable part of a lexical item is its ‘core’, and the other obligatory component is its ‘semantic prosody’.3 This is “a subtle element of attitudinal, often pragmatic meaning” (Sinclair 1998: 20), which determines the meaning of the whole unit. The optional categories ‘collocation’, ‘colligation’, and ‘semantic preference’ describe various aspects of the realisation of the lexical item. ‘Collocation’ is the co-occurrence of words, ‘colligation’ refers to the co-occurrence of grammatical phenomena, and ‘semantic preference’ is “the restriction of regular co-occurrence to items which share a semantic feature”. Sinclair (1998) illustrates the categories that characterise a lexical item with a concordance analysis of the word budge. Concordance 2.1 provides 30 randomly-selected lines from the 450-million-word Bank of English. Concordance 2.1 30 examples of budge from the 450-million-word Bank of English
English General Nouns
As Sinclair (1998) points out, and as the concordance sample illustrates, the word budge can describe the beginning of movement and it tends to be used in a negative sense: “[t]he point is that English does not talk much about budging at all, but about not budging” (Sinclair 1998: 16). Thus Sinclair (1998) identifies ‘NEG budge’ as the core of a lexical item, the abbreviation ‘NEG’ indicating that semantically positive occurrences of this word seem to be hard to find. The semantic prosody of the item involves the expression of frustration or irritation because something does not move. As collocates of budge, i.e. words that co-occur with budge, we can find, for instance, refuse to, won’t, would not. The word budge colligates with verbs, i.e. it tends to occur with this particular word class. The semantic preference describes the items that co-occur with budge with regard to the semantic features they share; thus we find a semantic preference of refusal or inability that expresses why someone or something does not budge. The categories collocation, colligation and semantic preference show an increase in abstraction, and Sinclair points out that for the semantic prosody of an item “there is often no word in the language that can be used as descriptive label for it” (Sinclair 1998: 20). Moreover, the possible surface realisations of a lexical item can be hard or even impossible to delimit. The flexibility of the whole structure, however, is what Sinclair (1998: 22) regards as “essential for an adequate lexical item” to capture the complex patterns of co-selection that occur in texts, and at the same time it is possible to list such lexical items in a lexicon with finite entries (cf. Sinclair 1998: 22). .. The Pattern Grammar Hunston & Francis (2000) define the ‘patterns’ of a word as “all the words and structures which are regularly associated with the word and which contribute to its meaning.” A word can have different patterns, and the same pattern can occur with different words. Thus generalisations about words can be described in a Pattern Grammar. To represent the patterns, Hunston & Francis (2000) use a coding that requires very little abstraction. They only refer to categories of the group and clause type, and to specific words. The major codes that they use are the following (cf. Hunston & Francis 2000: 45), in the Appendix you find a similar list, but with some additions specific to the present work. v: n: adj:
verb group noun group adjective group
Chapter 2. The corpus linguistic point of view
adv: that -ing: to-inf: wh: with quote:
adverb group clause introduced by that (realised or not) clause introduced by an ‘-ing’ form clause introduced by a to-infinitive form clause introduced by a wh-word (including how) used with direct speech
For instance, the coding ADJ on n represents a pattern in which an adjective is followed by the preposition on and a noun group. The upper-case ADJ indicates the word class whose pattern is focused on, italics mark specific words in contrast to coding symbols, in this case on, and n symbolises the noun group. Thus ADJ on n represents, for instance, the pattern of dependent that is illustrated in the following example: He’s always been very dependent on me. Another example of a pattern is V to-inf representing a verb followed by a clause which is introduced by a to-infinitive form, as in John began to laugh. A disadvantage of patterns, one could argue, is that the representation of lexical items remains incomplete. In comparison to the detailed description that Sinclair’s (1998) concept provides, patterns can only tell us very little about the idiosyncratic behaviour of words. Thus when Hunston & Francis (2000) talk about the patterns of a ‘lexical item’ they focus on surface elements that characterise the behaviour of a word. On the other hand, an important advantage of patterns is that they enable generalisations, as words which share pattern features can be grouped together. The two-volume COBUILD Grammar Patterns series (Francis et al. 1996, 1998) shows what this means in practice: reflecting corpus evidence, patterns of nouns, adjectives and verbs are listed; and for each pattern there are lists of words that have that pattern. However, the usefulness of the pattern approach would be questionable if the focus were on surface features only. Hunston & Francis (2000) point out that there is a strong association between pattern and meaning which becomes evident in two ways: if a word has different meanings they tend to be distinguished by different patterns, and if different words have the same pattern they tend to share an aspect of meaning. Thus Hunston & Francis (2000) divide the words that are found with a particular pattern into ‘meaning groups’. For the pattern ADJ that, for instance, adjectives such as amazed, bemused, puzzled can be grouped together under the heading ‘having a reaction to a situation’, while another meaning group that is concerned with ‘being certain or uncertain’ contains confident, dubious, sceptical (Hunston & Francis 2000: 93f.). Furthermore, it is possible to find meaning groups of different patterns that share an aspect of meaning. Different patterns that share the same meanings
English General Nouns
are collected in ‘notional groups’. Hunston & Francis (2000: 114ff.) identify, for instance, a notional group of ‘(Talking about) making someone do something’ where we find the pattern V on /upon n to-inf with the verbs call, or prevail as in So we call on everyone to seize this opportunity and to look at it positively, together with other patterns such as V with n to-inf with the verbs collaborate, connive, or contract as in I pleaded with her to stop but she wouldn’t. ... she conspired with others to perform illegal campaign services. Hunston & Francis (2000) take their approach as far as to abandon syntactic distinctions of clause elements and any grammatical terminology other than that explained above. In Chapter 6 of the Pattern Grammar, Hunston & Francis (2000) discuss a number of examples to illustrate problems of structural analysis and to question the usefulness of traditional structural distinctions. One of their examples is the pattern V from n (Hunston & Francis 2000: 162f.): (1) The service will depart from Inverness at 10:15 . . . (2) Many areas of the world would actually benefit from global warming. (3) He quoted from a medieval lament. (4) The mechanic drank from the bottle with enthusiasm.
In the first example Hunston & Francis (2000) see no problem in identifying the prepositional phrase as an adjunct, in the second example what follows the verb is viewed as a prepositional object, but for the remaining two examples Hunston & Francis (2000: 163ff.) point to a number of difficulties in finding an appropriate category. Another example in favour of a pattern analysis are patterns with finite clauses. In traditional grammars finite clauses can be analysed as clause elements. Example (5) would thus illustrate a pattern with one object and example (6) a ditransitive clause pattern. (5) He said the country was unstable. (6) She told me he’d planned to be away all that night.
Hunston & Francis (2000: 156) criticise that such an analysis downgrades the that-clause to “a mere component of the initial clause” and does not pay enough attention to the that-clause as a complete unit which in fact contains what is often the main information of the sentence. Following Sinclair, Hunston & Francis (2000: 156) regard the that-clause as “in a sense the ‘main’ clause of the sentence, with He said or She told me as a contextualising ‘preface”’. Such an interpretation can become clearer in a pattern analysis that simply characterises the examples as patterns V that and V n that. On the basis of the
Chapter 2. The corpus linguistic point of view
different kinds of examples that they discuss, Hunston & Francis (2000) finally argue that as soon as one starts to use structural terms, such as Object, Complement and so on, the exercise of analysis inevitably becomes both complex and of minimal usefulness in terms of the information it adds to the clause under analysis. (Hunston & Francis 2000: 176)
Thus Hunston & Francis (2000: 177) come to the conclusion that a pattern analysis should stand by itself and does not need to be related to more abstract categories. .. Lexical priming In his most recent work, Hoey (e.g. 2004a, b, c)4 has started to develop a theory of language that he calls ‘lexical priming’. With the theory of priming Hoey (2004a: 386) offers an explanation for the existence of collocation: “the only explanation that seems to account for the existence of collocation is that each lexical item is primed for collocational use”. Hoey’s (2004a) priming draws on psycholinguistic arguments and it claims that as the word is learnt through encounters with it in speech and writing, it is loaded with the cumulative effects of those encounters such that it is part of our knowledge of the word that it co-occurs with other words. (Hoey 2004a: 386)
Lexical priming not only accounts for collocation, but it can also describe everything that we know about a word. The notion of priming is based on the assumption that “the mind has a mental concordance of every word it has encountered, a concordance that has been richly glossed for social, physical, discoursal, generic, and interpersonal context” (Hoey 2005: 11). In addition to collocational priming Hoey (2004a) describes, for instance, the priming for grammatical categories, e.g. a word is primed for use as a noun. Another type of priming is ‘semantic association’ which “occurs when a word associates with a semantic set or class” (Hoey 2004a: 387), this type of priming basically covers what Sinclair (1998) describes as the semantic preference of a lexical item (cf. Hoey 2004a: 388). With regard to the present work, the most important point about Hoey’s theory is that it suggests a link between lexis and text by means of the textual priming of a word. The ‘textual colligations’ of a word describe its positive or negative preference with regard to textual properties (Hoey 2004b: 174). Hoey (2004b) makes the following five claims, which will be relevant to the discussion in the following section:
English General Nouns
1. Every lexical item (or combination of lexical items) may have a positive or negative preference for participating in cohesive chains. 2. Every lexical item (or combination of lexical items) may have a positive or negative preference for occurring as part of Theme in a ThemeRheme relation. 3. Every lexical item (or combination of lexical items) may have a positive or negative preference for occurring as part of a specific type of semantic relation, e.g. contrast, time sequence, exemplification. 4. Every lexical item (or combination of lexical items) may have a positive or negative preference for occurring at the beginning or end of an independently recognised ‘chunk’ of text, e.g. the paragraph. 5. If a lexical item (or combination of lexical items) has any of the above preferences, it may only or especially be operative in texts of a particular type or genre or designed for a particular community of users, e.g. academic papers. (Hoey 2004b: 174) One of Hoey’s (2004a, b) examples of textual priming is the word today, which is primed for cohesion and can be shown to occur in chains of time references, e.g. yesterday – last night – today – next week (Hoey 2004a: 405). The word today also illustrates the genre specificity of priming, as Hoey (2004a: 405) argues: today in chains of time references is primed to occur in newspaper texts. .. Lexis, grammar, and text: Differences in the corpus-driven approach All three approaches described above (Sinclair, Hunston & Francis, Hoey) are similar in that they give lexis centre stage in a description of the English language and base their arguments on the analysis of corpora. There are, however, some important differences. Sinclair’s (1998) descriptive categories enable the most detailed lexical description. Whereas Sinclair (1998) focuses on the idiosyncratic behaviour of lexical items, Hunston & Francis (2000) aim at generalisation and thus identify similarities between lexical items. Hunston & Francis’ (2000) generalisations result from treating a pattern as if it were “a framework into which words with a particular meaning could be slotted” (Hunston & Francis 2000: 86) and a pattern can be described as belonging to any of its elements. In this way lexical items can be compared on the basis of surface elements which also give an indication of the meaning of the words: words that share patterns also tend to share meanings (cf. above Section 2.3.2). However, with regard to the meaning of lexical items, the Pattern Grammar can only provide a partial picture: words that share patterns only share some
Chapter 2. The corpus linguistic point of view
aspects of meaning. As Sinclair’s (1998) conception of the lexical item makes clear, a detailed description of the meaning of an item has to account for the variety of its realisations. Then, however, as we go beyond the invariable core, comparisons across lexical items are not necessarily as straightforward as for Hunston & Francis’ (2000) patterns. Hoey’s theory of lexical priming offers another way of comparing lexical items. Among the primings that can characterise a lexical item we find ‘textual colligations’, the primings of an item for textual organisation. Hoey (2004b) suggests that if the claims about textual priming were to prove correct, it would be possible to describe the language from a text-linguistic point of view: each word could be characterised in terms of its textual colligations so that it could be compared to other words of the language. Hoey (2004b: 174f.) suggests a ‘giant matrix’ for this comparison where the five textual primings are the lines of the matrix and each word is characterised by a column that contains the values ‘positive’, ‘negative’ or ‘neutral’ for each of the first four primings; and an indication of the genre, which characterises the fifth type of priming. There is a fundamental difference between the comparison of words in patterns and the comparison of primings. Patterns start with the surface features that characterise the narrow context of words, and a description in terms of patterns is derived bottom-up from the observation of words in the corpus. In contrast, Hoey’s (2004b) comparisons involve a higher degree of abstraction. His broad types of primings are not the result of the investigation of lexical items; the checklist to characterise an item has been established before the corpus analysis starts. Within the broad category of a textual priming, a more idiosyncratic characterisation is possible, e.g. the type of cohesive relation can be specified, as we have seen with the example of today; or the type of semantic relation that characterises an item can take a variety of forms, e.g. contrast, exemplification (cf. Section 2.3.3). Still, on the whole, Hoey’s theory of priming may be criticised for proceeding too fast with abstract categories for the description of the phenomena he finds in his corpus. For instance, the priming for grammatical function may describe a word as being positively or negatively primed for Subject function in clauses (cf. e.g. Hoey 2004a: 390). In contrast, Hunston & Francis’ (2000) approach is more radically corpus-driven. As we saw in Section 2.3.2, the Pattern Grammar takes a critical stance towards functional interpretations in terms of clause elements, offering a pattern analysis as an alternative. The differences between Hunston & Francis’ (2000) and Hoey’s approach are more complex than the above discussion suggests, and it would be too easy to focus on the type of criticism that has been hinted at. Patterns characterise
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local contexts of words, and for these contexts they can describe meanings. Patterns offer also possibilities to describe texts, as Hunston & Francis (2000) illustrate. An analysis of text may view some instances of patterns in terms of constituency grammar, and in other cases it seems more appropriate to describe patterns linearly as flowing from one lexical item to the next, or as pattern strings that occur with overlapping (cf. Hunston & Francis 2000: Ch. 8). Such configurations, however, still refer to narrow contexts and it may be argued that the generalisations of the Pattern Grammar make it difficult to describe textual functions of lexical items (cf. for instance Chapter 4 of the present work). Hoey (2004b: 171) admits that the evidential base of his claims only allows for tentative statements, but for detailed textlinguistic analyses of corpus data this is inevitable. A functional description of the type required by Hoey’s approach needs careful human interpretation and is thus time-consuming. However, Hoey makes a claim that is of central importance: features of lexical items and properties of texts are related. Corpus linguistics seems to have focused so far on the relation between lexis and grammar and on quantitative accounts of features of texts (cf. e.g. Biber 1988), whereas textlinguistic questions have only received little attention yet (but see for instance Francis 1994; Partington 1998; Stubbs 2001a, 2001b; Partington & Morley 2002; Mahlberg 2003). Similarly, in textlinguistics lexis has not been given a central role, although organisational and functional features of lexical items have been identified (cf. e.g. Winter 1977; Tadros 1994). With the link between lexis and textlinguistics that Hoey presents in his theory of priming, he suggests that corpus linguistics may be “the key to the future of text-linguistics” (Hoey 2004b: 173). The link between textlinguistics and corpus linguistics also seems to be the answer to the question of the study of general nouns, but after the discussion of the present section it seems that we are back again where the present chapter started: there is still the practical question of how a corpus study should proceed. We could take Halliday & Hasan’s (1976) examples and work through the checklist of lexical primings, but on the basis of the above arguments this may boil down to just another version of a corpus-based approach as was outlined in Sections 2.1, 2.2.1. On the other hand, Sinclair’s (1998) description of the semantic prosody of a lexical item, which accounts for the way in which a lexical item ties in with other items in text (cf. Section 2.3.1), and which could be described as coming close to the function of an item in text (cf. Sinclair 1996: 87f.), seems to be encouragement for a corpus-driven stance: lexical items play a role in the organisation of texts, but this role may be characterised by idiosyncratic patterns of co-selection that are specific to an individual item –
Chapter 2. The corpus linguistic point of view
and maybe more specific than a description that characterises its role in cohesive chains. Thus a corpus-driven approach would be necessary to discover idiosyncratic patterns. On the whole, it seems that a corpus linguistic analysis of general nouns can only find a starting-point if we have a closer look at theoretical claims about language in relation to corpus-driven methods. The following section will suggest such a corpus theoretical approach that will yield criteria for a corpus study of general nouns.
. A corpus theoretical approach to general nouns Linguistic controversies that marked the beginning of the corpus revolution may be described as the opposition between the arm-chair linguists and the corpus-linguists (cf. Section 2.1). As the corpus linguistic study of language has progressed, a new opposition has developed between corpus-based and corpus-driven approaches (cf. Section 2.2.1). It seems that in the generation following Fillmore’s corpus linguist (cf. Section 2.1), there are armchair corpus linguists who still have their comfortable theories, and radical corpus linguists who question everything linguists have said before. As hinted at in previous sections, in practice, the situation is more complex. Especially with regard to textlinguistic questions, appropriate corpus linguistic methods are difficult to identify. Section 2.4.1 will outline a corpus theoretical framework that summarises basic assumptions about the nature of meaning as well as about methodological principles. On this basis, Section 2.4.2 develops a corpus theoretical approach to the study of general nouns. .. The corpus theoretical framework The corpus theoretical framework stresses two points that may not be immediately obvious from the brief definition of the corpus-driven approach in Section 2.2.1: a corpus-driven approach to linguistics has to be based on a theory, and intuition plays an important role. These points are connected by the claim that language description is mainly concerned with meaning. In a nutshell, the following are the main arguments that form the basis for the present work: language is a social phenomenon, and meaning is defined as use. Meaning becomes observable through the repeated patterns of words, which are visible in corpora. The association of meaning and form is the main justification for giving priority to corpus-driven methods and a bottom-up description of lan-
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guage. As the words in a corpus can only give a partial picture of the functions of language in the discourse of a language community, interpretation plays an important role. A corpus theoretical approach to the description of language is by nature dynamic; it is constantly developing as new information is added to the development of the theory. I will outline these points in more detail. For the time being, a corpus linguistic theory seems to be best regarded as the rationale that governs the investigation of data and that determines how the results of the investigation are accommodated within a language description. This rationale deals with standards of adequacy of the language description, and identifies basic assumptions about language. It thus provides a framework for sketching the aims of individual corpus studies. The rationale will have an impact on what is focused on, on methodological decisions and descriptive categories, as well as on the relationship with other theories, which may be necessary to complement the bottom-up description. Thus, a corpus linguistic theory accounts for the basic framework of a language description and provides the rationale that governs the steps on the way to developing the description. A fundamental aspect of a theory is to define the object of study. What corpus linguistics can describe is language as it is documented in a corpus. It can create a model that reflects what the corpus illustrates: language in use. Thus not only are problems avoided that derive from theoretical dichotomies such as ‘competence – performance’, but also precision is possible with regard to the variety of language that is characterised. At the same time, the close relationship between the evidence and the model based on this evidence raises questions of generalisability with regard to the language as a whole. For the present study it will also be crucial to view the results with regard to the basis on which they are derived. This point will be developed in later chapters. The centrality of recorded evidence does not mean that only the words on the computer screen play a part in the development of a language description. An important aspect of the quality of corpus data is its ‘naturalness’ (cf. also Sinclair 1984), which distinguishes corpus data from invented or ‘interesting’ examples used as linguistic data (cf. Section 2.1). Naturally occurring instances of language are used by people in real life. Language is used to communicate and to act in a variety of situations with a variety of purposes. The focus on the social dimension of corpus data forms the basis for theoretical statements that characterise the place of corpus linguistics in language description:
Chapter 2. The corpus linguistic point of view
Corpus linguistics is based on the concept that language is a fundamentally social phenomenon, which can be observed and described first and foremost in the empirical data readily available, that is communication acts. (Teubert 1999: online)
The focus on language in use naturally entails a functional perspective that is concerned with meaning. When people use language they are interested in meaning and not in structures. While “recent linguistic theories have often not recognized that anything is being said at all” (Stubbs 2001a: 20f., quoting from a talk by Pawley), corpus linguistics is prepared to accept that “[t]he main function of language is to mean” (Teubert 1999: online). A corpus linguistic approach regards meaning as a linguistic phenomenon: meaning is realised in text and it cannot be described without the context in which it occurs. Tognini Bonelli (2001: 157ff.) finds support for these points in Firth’s theory of meaning which stresses that language use cannot be isolated from the context of situation: speech sequences operate “in contexts of situation which are typical, recurrent, and repeatedly observable” (Firth 1957: 35). Recurrent contexts affect the creation of meaning, and the meaning of an element in a text comprises “the history of its previous occurrences” (Teubert 1999: online). Repeated occurrences of words form the basis for the description of meaning. Repeated occurrences of words illustrate patterns that are associated with meanings. As argued in Section 2.3, corpus-driven approaches have so far focused on local associations between meaning and form. The claim that “form and meaning cannot be separated because they are the same thing” (Sinclair 1998: 12) also holds for the broader context of words, the texts in which they occur. As Halliday (1970: 326) puts it when he describes the textual function of language: “it is only because we can select the desired form of the message that we can also use language effectively both to represent and experience and to interact with those around us”. The multifunctionality of words makes a bottom-up description of lexical items increasingly difficult as we move beyond their narrow contexts. This difficulty was pointed out in the description of the semantic prosody (cf. Section 2.3.1). The broader the context, the more interpretation is involved in the description of meanings, and complex meaning relations may require abstract concepts to describe them. This situation points to the relevance of pre-corpus theories to complement the textual dimension of corpus linguistics. ‘Pre-corpus’ theories are understood here as theories that are not primarily derived from the investigation of corpus data and are (not yet) part of the corpus theoretical framework. Concepts from textlinguistics and discourse analysis
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seem to be a good starting-point to complement a corpus-driven approach. Textlinguistics and discourse analysis have always been based on the extensive study of texts. However, instead of analysing enormous amounts of data, the focus is on in-depth investigations of individual examples. Hoey’s theory of lexical priming shows how textlinguistic concepts can be combined with a lexical approach to the description of language. In this way he indicates a new dimension to textlinguistics by shifting the emphasis to lexis. Hoey provides a theory with far-reaching explanatory claims. As a consequence, the detail that can be given to textual features of individual items is at the present stage of his theory, which has only just started its development, limited. The present work is more narrowly focused than Hoey’s theory. In line with his theory, the focus is on the link between lexis and text, but the approach is more fundamentally corpus-driven, starting from the words in texts. To find a corpus-driven approach to general nouns, the ‘cyclical principle of minimal assumptions’ is applied. In his work, John Sinclair has always stressed that only minimal assumptions should govern a corpus analysis (cf. also Teubert 1999). Sinclair (1994) advocates that: we should trust the text. We should be open to what it may tell us. We should not impose our ideas on it, except perhaps to get started. We should only apply loose and flexible frameworks until we see what the preliminary results are in order to accommodate the new information that will come from the text. Sinclair (1994: 25)5
In the present work, the cyclical principle of minimal assumptions describes how a theoretical problem (or a hunch) can form the basis for a corpus study: the problem is reduced to minimal assumptions that are compatible with the corpus theoretical approach. On this basis, a methodology is developed for a corpus analysis. Preliminary results of the corpus analysis may trigger further questions and require pre-corpus theories for the discussion of corpus findings. Descriptive categories will constantly be tested and adjusted so that the study proceeds in a cyclical fashion. The results of the corpus study may also affect the development of the corpus linguistic theory. The cyclical principle of minimal assumptions stresses that a corpus-driven approach does not automatically disregard existing linguistic concepts just because priority is given to data. Even the strongest advocates of a corpus-driven approach concede that “the accumulated insights of centuries of research are not to be put aside lightly – but they are to be re-examined in the new frameworks” (Tognini Bonelli 2001: 179). Section 2.4.2 will outline the minimal assumptions for general nouns in de-
Chapter 2. The corpus linguistic point of view
tail. The present section concludes with more basic points about the corpus theoretical framework, which will accommodate the results of the study. In a very brief and simple way, we may say that major linguistic units that are typically identified are words, sentences, and texts, corresponding to the disciplines of lexicology, grammar/syntax and textlinguistics/discourse analysis. Corpus-driven work argues for a language description in which lexis gains in importance, and new types of units are identifiable. Thus, it seems useful to leave the idea of separate descriptive levels and move to a more integrative approach. As is often done, I will use the term ‘grammar’ in the sense of a systematic description of a language. To specify what ‘systematic’ means, for the time being, I would like to propose the following definition: a grammar is a set of generalisations about the behaviour of words in text. In opposition to this concept, ‘lexis’ can be understood as the set of lexical items of a language. Based on the link between lexis and text, textual statements can be included in this grammar as features of lexical items. On the basis of the results of the corpus study, this idea of grammar will be developed in more detail in Chapter 8. .. Minimal assumptions for the study of general nouns The present study aims at a corpus theoretical approach to general nouns: the corpus study is corpus-driven, and the corpus theoretical framework is the basis on which the method of the study is designed. The previous chapter introduced the cyclical principle of minimal assumptions that enables the study of general nouns. According to this principle, the corpus study has to start with only minimal assumptions about features that characterise general nouns. The two key features that characterise Halliday & Hasan’s (1976) general nouns are the general meaning of the nouns and their cohesive function. Halliday & Hasan (1976) draw on paradigmatic arguments to illustrate the ‘general’ meaning of their nouns. They compare general nouns to alternative nouns that could have been used in a given example. Furthermore, general nouns are compared to pronouns, thus the discussion raises the question of the categorisation of words into word classes. These arguments tie in with contextual criteria that characterise the cohesive function, i.e. the relation between a general noun and an element in its context. Chapter 1 showed how different strands of Halliday & Hasan’s (1976) arguments are taken up in the literature or how they are related to similar approaches. Although such observations may raise interesting questions and we could add a number of details to some of the ongoing discussions, the points that were summarised in Chapter 1 are not automatically relevant to the initial steps of a corpus-driven study. It seems difficult, for instance, to
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find a link between a corpus linguistic approach and purely paradigmatic arguments as they may be employed in the discussion of a cohesive continuum. We saw in Section 2.3 that Sinclair (1991) argues that in the creation of text, the idiom principle takes priority over the open-choice principle: the choice of words in texts depends on the choice of other words. A corpus linguistic theory is built on the evidence from corpora and this evidence is an indication of what is used in language and what really occurs. Corpus linguistics cannot work with the same hypotheses that are possible in constructed examples of cohesive clines, but corpora make it possible to compare actual occurrences. Criteria for contextual features of general nouns that are suggested by the literature may be equally difficult to reconcile with the principle of minimal assumptions. As pointed out in Chapter 1, the focus on particular determiners and modifiers for the cohesive uses of general nouns has already been proved to be too restrictive. Other approaches to subgroups of nouns may characterise the relationship between a noun and its context with the help of cognitive linguistic arguments. Schmid (2000) presents a large-scale corpus study of ‘shell nouns’. Shell nouns overlap to some extent with general nouns (cf. Schmid 2000: 10). The selection criteria for his ‘shell nouns’ are motivated by the functions that define these nouns. With regard to information that is expressed in stretches of text, shell nouns can, for instance, serve the function of ‘temporary concept-formation’. “This means that they allow speakers to encapsulate these complex chunks of information in temporary nominal concepts with apparently rigid and clear-cut conceptual boundaries” (Schmid 2000: 14). Schmid (2000) relates the functions of shell nouns to textual patterns. Thus the pattern ‘noun + that’, for instance, can be used in a corpus study to select potential shell nouns. As argued before (cf. Section 2.1, 2.2.1), pre-defined patterns seem to be too restrictive for a corpus-driven study of general nouns. Equally, for the interpretation of corpus data, cognitive linguistic arguments will not be referred to. In Chapter 4 an example is given of how corpus linguistic evidence may even raise questions about cognitive linguistic lines of argument. The corpus theoretical approach of the present work starts from surface features of texts. Interpretation is necessary in the descriptions of patterns in text, but no explanatory claims about brain processes are made. With regard to the corpus theoretical background, the principle of minimal assumptions results in the following approach to general nouns. The main starting-point is the definition of meaning as use. Meaning is found in texts, and patterns in texts make meaning observable. This approach to meaning views language as a fundamentally social phenomenon (cf. Section 2.4.1), a
Chapter 2. The corpus linguistic point of view
point that will play a central role in the discussion of the present work. The definition of meaning as use forms the basis for two main assumptions: 1. General nouns are frequent nouns. 2. General nouns are characterised by local textual functions. Central to both assumptions is the comparative nature of corpus linguistic statements. Although corpus linguistics cannot discuss relations between nouns in terms of alternatives in a given situation, corpus linguistics can compare nouns on the basis of their frequency of occurrence. If meaning is defined as use, frequency is part of the meaning of words. Frequent use may thus be interpreted as general meaning. Frequency counts alone cannot describe meaning. Frequency has to be interpreted, so that the words are related to their contexts. In the present study, frequency is a selection criterion to identify nouns that seem promising for an in-depth investigation. Thus the ‘frequency assumption’ is inseparably linked to the second assumption, ‘the context assumption’. According to the context assumption, textual patterns of nouns can form a basis for their characterisation. In a similar way to Hoey’s theory (cf. 2.3, 2.4.1), lexical items are thus viewed in relation to textual properties. More specifically than in Hoey’s framework, it is assumed that textual functions can be defined bottom-up in relation to lexical items. This is what makes the functions ‘local’. From a purely corpus-driven point of view – i.e. without the complementary descriptive apparatus of textlinguistics that is used in Hoey’s theory – the context assumption claims that there is a middle way between the detailed description of a complete lexical item, as in Sinclair’s theory, and the generalisations of Hunston & Francis’s (2000) Pattern Grammar. This middle way could be the key to the characterisation of general nouns. If the description is less detailed than for a complete lexical item, it is possible to compare nouns. If the description is more detailed than the Pattern Grammar description, it is also possible to compare nouns, but not only with regard to their pattern context, but also with regard to textual functions. A consequence of the context assumption is that the characteristics that describe the cohesive function of Halliday & Hasan’s (1976) general nouns do not play a role in the initial stages of the corpus study. If a noun is typically linked to other elements in its context, this will become obvious from the concordance analysis. And how this link is to be characterised will also depend on the corpus data. At the beginning of the study the term ‘local textual function’ was a fairly vague way of expressing that there might be some visible link between lexical and textual properties of a word. When formulating the initial assumptions, it
English General Nouns
was felt that a descriptive tool other than those available in corpus linguistic approaches was necessary in order to be sufficiently open to what the text may tell us about general nouns. With the methodology that will be described in Section 3.3 contextual features of nouns were observed that gave shape to the concept of local textual functions and Chapter 8 will eventually show how local textual functions can be seen as a contribution to the corpus linguistic theory outlined in the present chapter. Implicit in the two assumptions is a third: general nouns are nouns. It is assumed that words can be divided into classes and it is assumed that there is something such as a class of nouns, which has a subclass of general nouns. The outline in the present section shows that the ‘minimal’ assumptions are in fact highly complex. Chapter 3 will discuss methodological consequences of the points made here.
Conclusion The present chapter has stressed the advantages of a corpus linguistic language description. Corpora can bring to light facts about language that may be hidden from our intuitions. Central is the observation that units of meaning tend to be more than single words, and lexical patterns characterise the combinations of words in texts. The information that is derivable from corpora depends on the method that is applied to investigate the data. The present approach aims at a corpus-driven study of general nouns. Corpus-driven work is not set in a theoretical vacuum. A corpus linguistic theory has been outlined as the basis for the study of general nouns. The fundamental claim of the theory is that language is a social phenomenon, and that meaning is definable as use. The cyclical principle of minimal assumptions links the problem of general nouns to the corpus theoretical background. The frequency assumption and the context assumption about general nouns form the starting-point for the corpus study.
Notes . There would be much more to say on the terminological variety used to describe collocational phenomena of sequences of words. Terms other than lexical bundles or frames, are for instance, ‘n-grams’, ‘clusters’ (cf. Scott 2004), or ‘chains’ (cf. Stubbs & Barth 2003).
Chapter 2. The corpus linguistic point of view . The concept of the lexical item was suggested even earlier in Sinclair (1996), but Sinclair (1998) expands on the theoretical context of the concept. . For the term ‘semantic prosody’ see also Louw (1993). . At the time of writing, I first learnt about the theory of lexical priming through presentations that Michael Hoey gave at various conferences such as ICAME, TALC, or Corpus Linguistics and the articles that are referred to in the present chapter expand upon some of these presentations. Michael Hoey’s book Lexical Priming. A new theory of words and language brings together many of the ideas that he has been developing in relation to different aspects of lexical priming. The monograph only appeared a few weeks before the present book went into print, so I kept the references to the earlier articles and did not try to replace them by references to the more recent publication. In the present work, when I talk about ‘Hoey’s theory’ without providing a precise date this is meant to refer to the more general features of the theory as they are presented across different publications. . John Sinclair has recently published a book with the title Trust the Text (Sinclair 2004b). This collection of articles contains among others, the articles that are referred to in the present book as Sinclair (1994), Sinclair (1996), and Sinclair (1998).
Chapter 3
Minimal assumptions in practice Interpreting corpus data
Introduction The overall principle guiding this study is ‘trust the text’ (cf. Section 2.4.1). The previous chapter stressed that completely theory-free observation is almost impossible, and any method of simply ‘looking at’ text will depend on a theoretical framework. The present chapter deals with the methodological details of the minimal assumptions of Section 2.4.2. Fundamental to corpus studies is the selection of the data on which generalisations are based and Section 3.1 will provide some brief information on the corpora used in the corpus study. Chapter 3.2 focuses on issues of frequency and the selection of the nouns for the present study. Section 3.3 outlines the methodology of the concordance analysis. The points of the present chapter highlight a central issue in corpus linguistics that Hunston & Francis (2000) describe in the following way: Potentially, then, we have two competing (or complementary) sets of generalisations arising from a corpus, one that depends entirely on frequency of co-occurrence and is able to be generated by computer software alone, and one that is more interpretative and demands the input of a human researcher. How these sets of generalisations might differ from each other, and the implications of such difference, are topics that have yet to be explored. (Hunston & Francis 2000: 27)
The present chapter deals with this problem in order to prepare the ground for an investigation of general nouns.
. The corpora of the present study In a corpus-driven approach to the description of English, the data is central for the justification of statements about tendencies in the language. In the area
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of corpus design and compilation, the term ’representativeness’ is used to refer to the extent to which the results of a corpus analysis allow for generalisations to be made which apply to the language as a whole (or a language variety) (cf. e.g. Biber 1993; Biber et al. 1998: 246; Kennedy 1998: 62; Leech 1991: 27; Renouf 1987: 2). The problem, however, seems to be to find precise criteria for representativeness. Among the factors that are typically discussed are the size of the corpus, the size and the types of the texts that it contains, as well as the proportions of the components of a corpus (cf. e.g. Kennedy 1998: Ch. 2.5; Atkins et al. 1992). As is argued in Mahlberg (forthcoming, a), it seems reasonable to take a pragmatic approach to the issue of representativeness: any corpus should be viewed in relation to the purpose for which it is used, and what counts is to know what the corpus contains and to be aware of potential effects that this content may have on the results of a corpus study. The present study aims to describe general nouns with regard to mainstream British English, and the corpus that is used is the British English component of the Bank of English. The corpus is held by HarperCollins in Glasgow. It developed from the Birmingham Corpus that was used in the Cobuild Project, a joint project by the University of Birmingham and Collins Publishers. The Bank of English is regularly updated and has been continually increasing in size. When the present book went into print, the Bank of English contained 450 million words of British, American, Australian and Canadian English. For my study, I used the Bank of English corpus from October 2000 which contained 418 million words, of which 307,087,676 words made up the British English component. The data of the Bank of English originates mostly from 1990–2000 and is intended to reflect the mainstream of current English (cf. Krishnamurthy 2002). The corpus consists mainly of journalistic texts (newspapers, magazines, and radio broadcasts), but it also has books (fiction, non-fiction, and academic), and an informal speech component. For the selection of the nouns, I used additional frequency information from the British National Corpus (World Edition). The BNC contains approximately 100,000,000 words and is a static corpus, i.e. its size and composition are fixed. The two corpora not only differ in size but also in their design criteria. The BNC is regarded by some as a ‘balanced’ corpus, because much effort went into the selection of appropriate categories and proportions of texts (cf. e.g. Burnard 2002), whereas the Bank of English is sometimes criticised for being too opportunistic because of the heavy reliance on journalistic texts. However, another way to view journalistic texts is to see them as representing mainstream English. Another difference is that the Bank of English mainly contains full texts, whereas many texts of the BNC are only samples of larger texts. In the following, when I talk about the
Chapter 3. Minimal assumptions in practice
Bank of English only the British English component is meant. It has to be noted that although both the Bank of English and the BNC contain transcriptions of spoken language, the results of the present study will be applicable primarily to written language, as the written component makes up the largest part of both corpora.
. Frequency The frequency assumption requires the corpus study to focus on frequent nouns. Rank ordered corpus frequency lists from the Bank of English and the BNC will provide the basis for selecting 20 nouns. Frequency lists are generated automatically by the computer. Section 3.2.1 starts with an overview of the theoretical considerations that concern the counting of ‘words’. The minimal assumptions view frequency in relation to meaning, and Section 3.2.2 describes the information that frequency lists can provide. It will be stressed that frequency is relative, and depends on the texts from which it is derived. The discussion of key words shows how frequency lists can create assumptions about meanings in texts. The basic arguments of this discussion will underlie the interpretations in Chapters 4 to 6. The selection of the nouns, however, seems to work best with simple frequency lists only (cf. Section 3.2.3). The choice of the 20 nouns of the present study is based on comparing frequency information from the Bank of English and the BNC (cf. Section 3.2.4). .. What does the computer count? The repetition of words and combinations of words that can be observed in corpora enables statements to be made about typical uses and thus about the meanings that are found in a language. However, for some basic questions we are still a long way from finding the ultimate answers: for example, which units are to be counted, as well as how to interpret such quantitative information. Quantitative data is generated by computer tools focusing on surface features of language. Any interpretation of frequencies will have to take into account factors that shape the type of information the computer provides. The following are some basic points about quantitative information from corpora. The list is far from complete but it suffices to illustrate the fundamental problem. When a computer counts ‘words’ this usually means the computer counts sequences of letters bounded by spaces. The computer identifies a ‘type’ when the same sequence of letters occurs repeatedly. The number of types is the num-
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ber of different words in a corpus or text sample. Repeated occurrences of the same type make up the number of ‘tokens’ of that type. So far, only surface criteria are involved. As soon as criteria of meaning come into play, the situation becomes more complex: different types may be related. For a native speaker of a language it will be clear, for instance, that go and going are related. Such relations can be accounted for by ‘lemmatisation’, i.e. “classifying together all the identical or related forms of a word under a common headword” (Kennedy 1998: 207). Thus the lemma of GO includes the words go, goes, going, went, gone. Another point refers to identical sequences of letters having different meanings. Such words may be called ‘homographs’ and a typical example is bank, which can refer to a financial institution but can also be used to talk about the bank of a river and, as a verb, to describe the movement of an aircraft. Furthermore, the interpretation of frequencies involves the interpretation of units of meaning that are more than a single word. How are units such as bank account or bank on treated in frequency counts? These examples only involve two words. Chapter 2 dealt with even more complex units of meaning. In particular, the concept of semantic prosody illustrates the great extent of variation that is involved in the patterns of lexical items. Thus the phenomena that are counted by a computer are only a simplification of the actual situation of language. A point about frequency information that is different from the identification of appropriate units to be counted is the interpretation of the distribution of these units: is a particular word distributed evenly across the texts in a corpus? Leech et al. (2001: 17ff.), for instance, suggest some statistical measures to describe the distribution of words, and the Plot function in Scott’s WordSmith (Scott 2004: online) offers one way of visualising the distribution of words in texts. The fact that the computer processes surface phenomena in the first place is related to an important area in corpus linguistics: the ‘annotation’ of corpora, i.e. the linguistic information which may be added to the ‘raw’ texts of a corpus (cf. also Chapter 2). A common way of annotating corpora is partof-speech tagging: each word type is assigned a label that indicates its word class. Depending on the type of information that is added, the annotation process can be carried out automatically to a certain extent. Annotated corpora can in turn form the basis for further processing of the data, e.g. lemmatisers can work with corpora that are annotated with word-class tags (cf. Leech et al. 2001: 15f.). Opinions on the usefulness of annotation vary. Annotation may be seen as ‘enriching’ a corpus with information, but it may also be interpreted as ‘corrupting’ the text with information that imposes a certain view on the data.
Chapter 3. Minimal assumptions in practice
A similar area where caution is needed is the use of statistics in the interpretation of corpus data. Statistical procedures work with assumptions about the distribution of words. Some assumptions may be better suited to linguistic analysis than others (cf. for instance the arguments in Baayen 2001; Leech et al. 2001: 16f.; Scott 2004: online; Danielsson 2001: 38ff.), but there will always be assumptions involved. However, the pervasiveness of co-selection and the flexibility of patterns of words make it difficult to assess which assumptions are closest to the situation of natural language. On the whole, depending on the research question, statistics can be helpful when large amounts of data have to be processed, but statistics are not of much value if they lack appropriate interpretation and are not complemented by contextual information and human evaluation. These are only a few of the points illustrating that any kind of frequency information is relative: it depends on the criteria that determine what is counted. It is neither possible nor necessary here to give a full account of all the factors that are involved in the web of relations affecting frequency information. Central to the present study, however, is that frequency information refers to surface phenomena in the first place, and its usefulness for a corpus study that is concerned with meaning will depend on the interpretation of the frequency counts in relation to contextual factors. In the present chapter, frequency will be dealt with as the starting-point of the concordance analysis: it is the selection criterion for the nouns that will then be investigated in a detailed concordance analysis. .. Frequency lists and key words Frequency lists are a basic form of frequency information, but they also provide important information to complement the results of detailed concordance analyses (as will become particularly clear in Chapter 7). Frequency lists can provide a general characterisation of the corpora from which they are drawn. Kennedy (1998: 97ff.) compares the frequency rank orders of words in six corpora to illustrate the type of information that can be derived from frequency lists. Table 3.1 is adapted from Kennedy (1998: 98f.): the rank orders of the Birmingham Corpus (Bham), the predecessor of the Bank of English (cf. Section 3.1), are compared to those of the Brown Corpus (Brown), LOB Corpus (LOB), Wellington Corpus (Well), American Heritage Corpus (AHC), and London-Lund Corpus (LL). The main differences between the corpora involve size, regional variety, time of text production, and representation of spoken and written language. Furthermore, the American Heritage Corpus is a corpus
English General Nouns
Table 3.1 Rank order of the 50 most frequent word types in the Birmingham Corpus compared with other corpora (adapted from Kennedy 1998: 98f.)
the of and to a in that I it was is he for you on with as be had but they at his have not this are or by we she from one all there her were which an so
of publications written for children. As Kennedy (1998: 97) points out, differences in rank ordering can be interpreted as reflecting differences in the nature of the corpora: a spoken corpus, for instance, is characterised by a high frequency of I and a relatively lower rank of had and were (Kennedy 1998: 97). Furthermore, Kennedy (1998: 97) uses the frequency comparison to stress a consistency among the lists: all of the words are function words, with the only exception of said. The prevalence of function words at the top of rank ordered frequency lists is typically found with large general purpose corpora. Kennedy (1998: 102) further points out that “[t]he more narrowly focused the corpus [. . .] the more content words find their way into the higher frequency levels”. Kennedy (1998: 101f.) illustrates this situation with the example of a 320,000-word economics text and a corpus of academic English consisting of 160 two-thousandword samples: in the single economics text 18 of the 50 most frequent types are content words, e.g. price, cost, demand, curve; in the corpus of academic English only three content words occur among the 50 most frequent types: use, make, year (in the corpora of Table 3.1 only said occurs among the top 50 words). The comparison of frequency lists also plays a role in the definition of ‘key words’. Mike Scott’s WordSmith Tools calculates key words by comparing the frequency list of a single text with the frequency list of a reference corpus. A word will figure as a key word of the text if its frequency in the text differs significantly from the frequency that could have been expected based on the frequency in the reference corpus. Key words are defined in purely statistical terms. The focus is typically on key words that are unusually frequent; words which are unusually infrequent are called ‘negative key words’. Scott gives the example of a reference corpus of assorted newspaper articles, against which a single one of its articles is compared; so that the KeyWords tool produces the
English General Nouns
key words squatter, police, breakage, council, sued, Timson, resisted, community. Scott (2004: online) points out that the KeyWords program typically identifies three kinds of words as key: there are proper nouns, there are words that human beings would identify and that “give a good indication of the text’s ‘aboutness”’, and there are high-frequency words such as because, shall, or already that may be indications of style. .. Frequency and general nouns The above examples of the interpretation of frequency lists, and the possibilities that the calculation of key words offers, could be taken as a basis to suggest more technical methods for the study of general nouns than a simple concordance analysis (as will be proposed in Section 3.3). However, as has been stressed in Section 3.2.1, the computer works on surface features of language. The relationship between frequency and meaning that is crucial to the present study requires us to see the nouns in their textual contexts, as the following arguments make clear. Kennedy (1998: 102) concludes from his comparison of rank ordered frequency lists across different types of corpora that “[f]or corpus-based studies of function words, a diverse corpus from a wide range of texts and genres is needed. For the description of content words, a more homogeneous (special purposes) corpus may be more valuable”. Kennedy’s (1998) argument about the distribution of function and content words may suggest a link to the flowing boundary that Halliday & Hasan (1976) describe between the two groups of words: function words tend to be more frequent than content words. Consequently, nouns that are found in frequency lists among the higher ranks are likely candidates for general nouns as they are closer to function words. This argument would support the minimal assumption of Chapter 2.5 to focus on the most frequent nouns in a study of general nouns. Moreover, Kennedy’s (1998) argument of the type of corpora that are needed for the study of function words in contrast to content words seems to be in line with the minimal assumption: Kennedy (1998) suggests the use of special purpose corpora for the study of content words. Thus a general purpose corpus such as the Bank of English seems to be better suited for the study of general nouns, which are assumed to be different from typical nouns and to some extent similar to function words, for which Kennedy (1998) recommends a ‘diverse corpus’. The basic idea of this argument is also reflected by Scott’s observation that, among the key words that WordSmith identifies, there are usually words that are an indication of what the text is about. If we assume that general nouns are to some extent similar
Chapter 3. Minimal assumptions in practice
to function words, it may be that the nouns which the KeyWords program lists in the middle area of a key word list, i.e. the words that are neither unusually frequent nor unusually infrequent in a text, are likely candidates to shed some light on the functions of general nouns. The words that occupy the middle ground in lists of key words make up a proportion of the text that is similar to the proportion of these words in the reference corpus. Thus they are not particularly characteristic of a specific text, but reflect the general tendency of the corpus. With such procedures we could preselect occurrences of the highfrequency nouns to increase the efficiency of an otherwise time-consuming concordance analysis. These arguments are convincing to some extent, but once again caution is needed. First of all we have to consider the fact that frequency is always relative: different corpora will result in different frequency lists, as Kennedy’s (1998) comparison of frequency ranks has shown. The results that the KeyWords program produces will also vary according to the reference corpus on which the comparison of the frequency lists is based (as well as on pre-set statistical parameters) and Scott warns us that “[t]he computer is not intelligent and will try to do whatever comparisons you ask it to, so it’s up to you to use human intelligence and avoid comparing apples with phone boxes!” (Scott 2004: online). If we start the analysis with too many assumptions about the types of texts and the reference corpus to be used for a key word analysis, the argument may become circular. Another point relates to the distinction between function words and content words that underlies the above arguments. Content words are typically regarded as central features of texts, “the main building blocks of texts”, while function words have an organising function (cf. Biber et al. 1999: 55). This view seems to imply that single words can give information about the content of a text, but the position of a noun (or better, a form of a noun) in a frequency list does not tell us much about meaning. The indication of the aboutness of texts and the application of key words in content analysis (cf. Scott: online) depend on the complementation by human interpretation. If we are shown a key word list where squatter, police, breakage, council, sued, Timson, resisted, community figure as key words, what we may guess about the text from which this list is derived is that the text is about a squatter, there is someone called Timson, there seems to be some conflict with the law, etc. But what does this tell us about the text? Is it Timson who called the police? Is Timson a squatter? Who is sued? As these key words characterise a newspaper article, we may develop our guess by our experience of newspaper articles and what they usually deal with, but we will never find out the true story unless we read the article and see how the
English General Nouns
key words are linked in the text. In Chapter 7 we will return to a more detailed discussion of the ‘meaning of a text’. What is important to an interpretation of key word lists is the directionality of the argument. As Stubbs (2001a: 143) points out: “The computer’s findings (frequencies, comparisons or graphs) are not an interpretation of the meaning of the text, but a presentation of some of its formal features”. Stubbs (2001a: 128ff.) analyses a short story and illustrates how key words can be interpreted as reflecting features of the text, but the statistics are only useful in combination with a human interpretation of the text, linking knowledge of the content that was gained by reading the story to the formal features that are illustrated by the statistics. What Stubbs (2001a) illustrates for the analysis of an individual text is also true for the use of frequency information in the discussion of general nouns: formal information of frequency has to be linked to contextual information in order to enable statements about meaning to be made. This is also the reason why the selection of nouns is based on frequency lists only, and does not work with statistical procedures that find, for instance, clusters for the words in the frequency list, i.e. “two or more words which are found repeatedly near each other” (Scott 2004: online), a concept which is similar to Biber et al.’s (1999) lexical bundles (cf. Chapter 2). Another option would have been to start with the most frequent two, three, four etc. word clusters/bundles, check which nouns occur in those sequences of words, and further analyse these sequences in concordances. All these methods could have increased the amount of data to be analysed in the corpus study, but they would have led to a loss of detail in the contextual analysis. .. The nouns in the corpus study The corpus study starts with word forms of nouns as they are found in a tagged frequency list. In the Bank of English the most frequent noun is time, occurring as word number 60 in a rank frequency list that is based on the tagged corpus. Table 3.2 focuses on nouns only, and shows the 62 most frequent nouns in the Bank of English. The second column presents the rank order of the respective word form in the BNC; a ‘+’ in the BNC column indicates that the noun does not occur among the top 62 nouns. The reason why Table 3.2 contains 62 nouns will become clear below. The frequency lists are not lemmatised, i.e. singular and plural of a noun are treated separately. The frequency lists as they appear in Table 3.2 do not include words that are tagged as proper nouns, except for those that may also have another noun tag, e.g. minister occurs with the tag for
Chapter 3. Minimal assumptions in practice
Table 3.2 Frequency ranks of nouns in the Bank of English and BNC
time year people years world way day government home life man week night part party country end money children women house place things work men company days team business side group family course game war number thing months west market month season
a proper noun as well as a singular common noun, although the tagging is not always consistent. The decision to work with a tagged corpus, and the choices that have been made in the editing of the lists, were in the first place pragmatic. The frequency list tags are useful to distinguish, for instance, word forms that can occur as a noun as well as a verb, e.g. move. It also has to be kept in mind that the underlying tagging systems of the two corpora differ in some of the distinctions they make. An important point about the selection of the nouns is the fact that a concordance analysis is time-consuming, and consequently the number of nouns that could be handled in the present study was limited. In order to base the selection of nouns not on the frequencies in the Bank of English alone, the BNC was used for comparative information in the choice of nouns. Combining information from independent corpora often seems reasonable in corpus studies (cf. e.g. Stubbs 2001a: 123) and in the previous section we have seen how frequencies can vary across corpora. As only a fairly small number of examples seemed manageable in the concordance analysis of the present work (about 15 to 20) the aim was to choose nouns that are typical of general purpose corpora. So for the choice of nouns two corpora were used. As only few
Chapter 3. Minimal assumptions in practice
nouns could be chosen statistical procedures to compare the frequency lists were neither necessary nor appropriate. The first group of nouns to be chosen seemed fairly obvious: time, year, people, years, world, way, day, life, man. These nouns are among the top 11 in the Bank of English and the top 10 in the BNC with only minor differences in frequency rank. In both corpora, time is most frequent, in both corpora years, day and life occupy the same position in the frequency list, for none of the forms year, people, world, way, and man is the difference in rank more than four. Other nouns that were selected are part, end, women, place, things, men, business, family, thing, times, and woman. Although nouns further down the list tend to show greater variance in rank position, for none of the forms part, end, women, place, things, men, business, family, thing, and times is the difference in frequency rank more than seven. Only woman shows a greater difference with rank 62 in the Bank of English and 91 in the BNC frequency list. However, it still seemed reasonable to include this form, as the plural women occurred higher up in the list differing by only three positions between the corpora. For man, men the situation is reversed: the singular precedes the plural, with the rank difference for the singular, however, being only three. Obviously, the selection criteria are not fully objective. It could be argued, for instance, that children should also be included as the difference in rank between the Bank of English and the BNC list is only 4 – the same as for end. Similarly, it could be asked why the argument that led to the inclusion of woman does not apply to days, too. After all, the singular day is selected for analysis. There is a simple answer to these questions: the reasons for such decisions are purely pragmatic. A group of 20 nouns appeared to be of a manageable size for a detailed concordance analysis so I had to make a choice. At the same time I wanted some variety, e.g. by including place, although the frequency difference is 7. Initially, I also included the noun government as it ranks place 6 in the BNC and 8 in the Bank of English. Throughout the study, however, the patterns for government were difficult to relate to the patterns found for the other nouns, so I will not discuss this noun in the presentation of the results, but focus on the 20 nouns listed above. Again, this decision is not to be understood as a theoretical one, and in Section 5.6 I will briefly hint at some of the characteristics of government. The aim was merely to arrive at a manageable amount of information to be presented within this book. As you will see in the following chapters, there is still a wealth of phenomena that the corpusdriven approach has to deal with. On the whole, the choice of nouns for a more detailed analysis seems reasonably motivated by their frequency and the sim-
English General Nouns
ilarities in frequency ranks for the two corpora, and within the scope of the present study the selected nouns seemed to be a useful starting-point.
. Context The context assumption requires an analysis of the selected nouns in their textual contexts. This investigation of the nouns is achieved through concordances. Section 3.3.1 gives a brief overview of basic issues in analysing concordance data. Section 3.3.2 focuses on the categories of classification that are applied in the present work. The main principle for the description of examples is comparison, and only basic terminology has to be introduced in the initial steps of the analysis. .. Analysing concordance data The more detailed part of the corpus study is the analysis of the selected nouns with the help of concordances. A ‘concordance’ is a way of displaying examples of a word form. Concordance software lists all (or a specified number of) the occurrences of the ‘keyword’ or ‘node’ (i.e. the form searched for) with a specified amount of context to its left and to its right. This display format is known as ‘KeyWord in Context’ or ‘KWIC’. There are various options that can help the researcher to interpret the data. The lines of the concordance can be sorted (e.g. alphabetically, according to the first word to the left of the keyword), and statistical information such as collocation measures can be computed. Whatever technical options the researcher makes use of, it remains an important point about concordancing that “[a] corpus, examined at first in KWIC format [...], is read vertically, scanning for the repeated patterns present in the co-text of the node” (Tognini-Bonelli 2001: 3). Repeated patterns are indications of the relationship between meaning and form. However, the identification of groups of words that function together as a meaning unit is not straightforward. Meaning relations are most obvious for repeated combinations of surface elements whose meaning depends on the elements occurring together. In Concordance 3.1, a subset of the concordance of place, the repetition of take and place is evidence of such a unit of meaning.
Chapter 3. Minimal assumptions in practice
Concordance 3.1 25 examples of place
Another unit of meaning in this set of examples is all over the place. Although there is no formal repetition in this concordance sample, we intuitively identify the words as functioning together, because of the dependency of the meaning of the sequence on the co-occurrence of the individual elements. Such obvious dependencies of meaning characterise idioms, which can be recognised without the evidence from corpora. For the example of take place, the dependency of meaning is also obvious, and would be easily identified even without the repetition of the example. However, it is doubtful whether by mere introspection take place would come to mind as one of the most frequent uses of place. To observe meaning relations between words that are less obvious from a single example, repeated examples are necessary. Still, co-selection patterns may not always be obvious even from several concordance lines. In Chapter 5 we will have a closer look at the noun woman. On the basis of 100 concordance lines for the word woman, patterns as striking as those for place are not visible. In Concordance 3.2 you find the 100 concordance lines for woman sorted according to the first word to left of the node word.
English General Nouns
Concordance 3.2 100 concordance lines for woman
Chapter 3. Minimal assumptions in practice
In contrast to the example of place which illustrated the pattern take place the concordance of woman does not show such obvious patterns of units of meaning with strong dependencies between the surface elements. What is clearly visible are word class patterns: the noun occurs with determiners and is modified by different types of modifiers. We can also see collocations, e.g. young woman or pregnant woman. A possible next step in the search for contextual clues could be a detailed collocation analysis. A collocation analysis is easily carried out by corpus tools. Using statistical procedures, the computer can identify words whose occurrence in the context of the node is more significant than could be expected on the basis of the overall distribution of words in the corpus. Such an analysis can yield collocates of woman that are not visible in the above concordance, e.g. beautiful woman and the analysis could support our intuition and show that married woman, which occurs just once in the concordance, is a significant collocation. However, the present study does not use statistical tools to complement the
English General Nouns
information of the concordance samples. Instead of broadening the amount of data to overall corpus frequency information, which is needed to calculate collocates, the context of the node word is extended. Longer stretches of texts are analysed for the noun woman, and sometimes even the whole text has to be taken into account in order to find textual patterns in which the noun is involved.1 Such a detailed study is more time-consuming than automatic processes, but it is also more revealing with regard to textual patterns. The question remains as to the number of concordance lines that should form the basis for observation. A method that adjusts the number of lines to the item under investigation could start with say 25 examples, then take another 25, and go on adding examples until not much new information is added by looking at more data. This is a method used for instance by Sinclair (1999). It may be easily applicable to a single noun; for a group of nouns, however, it does not seem practicable in a limited amount of time. If longer contexts have to be examined, the task becomes very time-consuming. Thus, for reasons of feasibility, only 100 concordance lines are selected per noun. Consequently, the results cannot be taken as a basis for a representative quantitative interpretation. Instead, the concordance analysis focuses on qualitative aspects, and the results have to be seen as suggestive rather than definitive. When, in the following chapters, numbers are referred to, they can only indicate tentative tendencies which may form the basis for further investigation. The examples of each noun were selected with the every nth procedure. .. Dynamic categories and ad hoc labels For each of the 20 nouns, 100 concordance lines form the basis of the corpus study. First, the concordances are analysed for each noun individually; then the preliminary results are compared across nouns. This comparison may lead to adjustments of categories for a single noun. Following Sinclair’s (1994) postulate to ‘trust the text’ (cf. 2.4.1), the only criterion guiding the analysis is the aim of finding groups of examples with similar functions, i.e. similar meanings in text. Categories to describe the examples are thus developed by comparison of the examples. The categories are not fixed beforehand, and are therefore ‘dynamic’, i.e. various possibilities of classification are taken into account and adjustments made as the analysis develops. Without fixed criteria, it is not always easy to see how examples are best grouped together. Words fulfil several functions in a text; thus there are several options for classification. The following are three examples of meaning relations:
Chapter 3. Minimal assumptions in practice
1. A meaning becomes visible because it occurs repeatedly with a specific combination of words. An example described above is take place. 2. There may be repetitions of words that do not immediately suggest a strong meaning relation, but closer inspection may lead to functional interpretations. An example is the sequence years of, which is interpreted as a means of giving emphasis to what follows the of (cf. Chapters 4 and 6). 3. There may be examples with similar meanings, but for which a formal similarity is less obvious. In Chapter 4, the following two examples are grouped together, because they have a similar meaning that is interpreted as ‘investing time’: (1) Shouldn’t he be devoting his time to one or the other to make sure . . . (2) . . . he was spending the day with another friend.
The study does not aim to find formal representations of these meaning relations. In the concordance analysis, examples in which the nouns are functionally ‘similar’ are simply collected in a group, and an ad hoc label is used to characterise the examples. For examples (1) and (2), ‘investing time’ is such an ad hoc label. Ad hoc labels involve a certain amount of subjectivity, but as they are closely linked to groups of examples, they will be sufficiently clear. This point is outlined in more detail in Section 4.5. Groups of examples are regarded as ‘functional groups’ as they bring together examples with similar functions. These groups form the basis for the description of local textual functions. From the brief look at the examples of place and woman it is clear that different nouns may require different approaches to capture the patterns that characterise their meanings and show similarities with other nouns. In the present chapter, the principles that have been developed in the concordance analysis can only be indicated in a sketchy fashion. In the following chapters, they will be explained in relation to the examples, which will give a much clearer picture. Section 2.2 stresses that the use of terminology as descriptive tool may have effects on the phenomena that are observed in a concordance. The ad hoc labels of the present study are an attempt to maintain an open approach to the data. The categories sometimes suggest interpretations that may deviate from common grammatical consensus, e.g. years of is only a part of a noun phrase. The use of rather provisional categories is encouraged by Hunston & Sinclair’s (2000) arguments for ‘local grammars’. Following Sampson (1992) and Gross (1993), Hunston & Sinclair (2000) argue that
English General Nouns
there are gaps in the coverage of grammatical structures achieved by a generalizable system of structural analysis and that these gaps require the development of an alternative approach in order to achieve a comprehensive treatment. (Hunston & Sinclair 2000: 75)
Hunston & Sinclair’s (2000) arguments also make clear that an open approach does not have to start from scratch. A corpus-driven approach does not try to re-invent the wheel simply by using different terms. As Teubert (1999: online) puts it: “[t]here is a broad consensus on the central tenets of syntax”; what needs closer examination are “the margins where the evidence can be presented and described in different ways and where it is possible to disagree with a particular definition”. In the present study, if syntactic terms are used without explicitly defining or questioning them, they are used in their ‘prototypical’ sense, i.e. following common consensus as represented by major reference works and textbooks. The ‘prototypical’ category that will be discussed in more detail is the word class noun. One of the central terms that are needed in the study is the ‘pattern’. This term will be used in several senses. It will refer to generalisations as they are made in the Pattern Grammar, but it is also used to describe examples that are collected in functional groups. These examples tend to be more specific than the generalised patterns of the Pattern Grammar, but they are also called ‘patterns’ in order to indicate that a group of words functions together as a unit of meaning, and these examples can often be regarded as a subcategory of the Pattern Grammar patterns. In the context of the discussion, it will be obvious which of the senses is meant (otherwise an explicit explanation is added). To describe a noun in a ‘textual pattern’, for instance, stresses that the contextual relations go beyond the narrow context that is typically accounted for in the Pattern Grammar. Another term that is needed in the discussion of the nouns is the ‘residual meaning’. Sinclair (forthcoming) defines the ‘residual meaning’ as a meaning “that is realised when a single word is cited; it has to be strongly enough associated with the particular word that is recalled on citation, and it cannot rely on people being able to imagine a suitable cotext”. The residual meaning is, for instance, relevant to the discussion of prototypical noun characteristics. As the approach to the concordance analysis is corpus-driven, the presentation of the results cannot follow a unified system that applies equally to all of the nouns. The nouns have different functions, so different descriptive criteria are required. The nouns are divided into three subgroups that are discussed in separate chapters. For each group, the criteria of the description will be ex-
Chapter 3. Minimal assumptions in practice
plained, and the structure of the chapter is determined by the requirements of the nouns. The concordance analysis will reveal characteristics of the selected nouns that provide arguments in favour of describing these nouns as ‘general nouns’; thus right throughout the discussion the nouns under analysis will be referred to as ‘general nouns’. However, it has to be kept in mind that the term may apply to different degrees to individual nouns and it is only in Chapter 7 that the results of the concordance analysis are summarised and linked back to the initial assumptions.
Conclusion The present chapter has shown that the frequency and context assumptions of Chapter 2 are more complex than the adjective ‘minimal’ may suggest. Frequency information has to be viewed with regard to what is and what can be counted. Words as surface elements of language can be taken as evidence of meaning, but the interpretation of words in their contexts is essential to statements about meaning. The computer can assist the human observer by counting, selecting and displaying words; but the computer cannot yield information about meaning. Against this background, 20 nouns have been selected for a concordance study, the results of which will be presented in the following chapters.
Note . For examples in Chapter 5 that are (considerably) longer than a concordance line, additional information on the source of the examples can be found in the Appendix (p. 196).
Chapter 4
Time nouns
Introduction The nouns time, times, year, years and day form the first subgroup of the 20 nouns of this study. In the following, I will call this group ‘time nouns’. It is doubtful whether speakers of the language would intuitively identify these nouns as nouns that occur frequently, but time actually figures as the most frequent noun both in the Bank of English and the BNC. In grammars and textbooks as well, time nouns are not likely to be used as examples of nouns, although they may be mentioned in the context of adverbials, as in for the first time, every day, etc. However, to view the textual functions of time nouns only in terms of time orientation is a simplification of their actual uses. Time nouns occur in a number of patterns that illustrate different facets of time meanings. The present chapter starts with an overview of the examples and will explain the criteria according to which functional groups have been identified. Three examples of functional groups will be discussed in more detail (cf. Sections 4.2, 4.3, 4.4) before the focus moves to features that characterise the time nouns as a group. The focus on functional similarities makes it impossible to define clear-cut categories of classification (cf. Section 4.5). At the same time the lexical point of view suggests descriptive categories that may be better suited than syntactic descriptions to capture functions of the nouns in texts (cf. Section 4.6).
. Time nouns – an overview The concordance analysis aimed to identify similarities between the nouns by comparing their functions in texts. When we try to define the meanings of time, times, year, years, and day in isolation from actual examples of use, a relationship between the residual meanings of the nouns becomes immediately obvious: we can measure time in days and years. A first overview of the concordances further shows that all of the nouns occur frequently in time adverbials.
English General Nouns
However, the present analysis will not use syntactic criteria as the basis for the classification of examples. Instead, the focus is on meaning similarities that characterise patterns of time nouns. The frequency of recurrent time expressions seems to be generally recognised, and may lead to an interpretation of some of the uses of time nouns as institutionalised and ‘quasi-grammatical’ (Quirk et al. 1985: 1451): (1) I’ve been working on this problem all year and I must find a solution before January when I’m due to go abroad for a month. (2) I’ve been working a long time.
Biber et al. (1999: 794) provide quantitative evidence of the frequency of time expressions, and point out that “[t]ime prepositional phrases often contain the same nouns to show duration or points in time”. The nouns combine with prepositions in frames such as at ____ time, for ____ year (s), in ____ year(s). Further examples of lexical bundles (cf. Section 2.2.2) identified by Biber et al. (1999) are at the time of, at the end of the day, most of the time, the last time I, by the time I. Whereas the recurrence of time expressions seems to be uncontroversial, opinions may vary as to the syntactic interpretation of some of these structures. A case in point involves structures with the verbs take and spend. In Quirk et al. (1985: 540), for instance, we find the following sentences illustrating adverbials of time: (3) It takes me only ten minutes to clean my car. (4) They spend ages just sitting in the garden.
However, there are also arguments for interpreting such time expressions as objects of the verb (cf. for instance, Biber et al. 1999: 714; Quirk et al. 1985: 541 Note). Further points are added to the discussion by considering combinations of verbs with time expressions as relatively idiomatic, e.g. have time, take (a long) time, take years (cf. Biber et al. 1999: 1026ff.). Such interpretations of the uses of time nouns raise a number of questions about descriptive categories, and may veil some of the meaning relations that will be discussed in the following sections. The functional groups of the present study aim to show similarities of meanings that become obvious by comparison of the examples. Each of the groups illustrates facets of a ‘time’ meaning that characterises functions of the nouns in text. This shared time meaning is part of the semantic prosody (cf. Section 2.3.1) of the examples in a functional group. I will return to this shared meaning in Section 4.5, as the arguments will be clearer when a number of
Chapter 4. Time nouns
Table 4.1 Functional groups of time nouns (total number of examples per noun: 100) functional groups
time
times
year
years
day
time orientation
44 all the time
49 at times
47 last year
69 in recent years
37 one day
–
12 1.3 times more likely
4 9 per cent a year
6 7 years old
3 529m gallons a day
investing time
11 devoting his time to . . .
–
–
3 took five years to . . .
1 spending the day with . . .
time passes
7 time is running out
–
–
–
1 the day had passed off
4 of our time
18 in times of recession
–
3 a few golden years
–
–
–
1 in the same year as
5 the first years
–
3 of the year
11 years of
measurement
history, life
school, university
evaluation, 4 text It’s time for organisation
–
combinations 15 half-time
3 lunch times
39 six-year period
–
21 match-day
other
18
6
3
24
15
13 a day when, of the day
examples have been discussed. Table 4.1 gives an overview of the functional groups: it shows how many examples of a noun belong to a functional group, and it gives examples. For each noun 100 examples have been analysed. The table summarises the results of the comparison of the concordance lines. As meaning is fuzzy, the functional groups cannot mark clear boundaries, and reflect a certain degree of subjectivity in the interpretation of the examples (cf. Section 4.6). To avoid too much detail in the following discussion, pragmatic decisions have sometimes been required: only if there are more than three ex-
English General Nouns
amples of a noun that share a function is a category defined; if the number of examples for a single noun is less than four, a functional group will only be considered if there are similar examples for another noun. Take, for instance, the functional group measurement (functional groups will be indicated in bold). There are only three examples of day in this group, but as there are examples of times, year, and years with similar functions, a functional group is defined. These quantitative arguments are purely pragmatic, in order to focus on the main tendencies. The measurement group further illustrates the third type of meaning relation indicated in Section 3.3: ‘similar meanings’. A formal similarity between years in 7 years old and year in 9 per cent a year is less obvious, but in both examples it functions as measurement. It will be an important point of the present chapter to discuss various aspects of the relationship between meaning and form. I will start with a brief overview of the seven functional groups that have been identified, before moving on to a discussion of three of them in more detail. The labels of the functional groups given in Table 4.1 are ad hoc labels of a provisional nature: they aim to reflect the meaning distinctions on which the groups are based. The labels will be discussed in more detail in Section 4.5. The eighth group in Table 4.1 is a marginal category that is not treated as a functional group; the label ‘combinations’ reflects the formal features of this group (cf. the explanation below). The group other contains all remaining examples. For each of the time nouns the 100 concordance lines on which the following observations are based can be found in the appendix to this chapter.
Time orientation Most of the examples of time nouns that are classified as time orientation occur in or as time adverbials, but it will become clear that the definition of this group is different from the syntactic category time adverbials. This group will be discussed in detail below.
Measurement Whereas the units of time orientation focus on time itself, the units of the functional group measurement express time to measure or compare something other than time. Patterns in this group are a day/year to express a reference point for a measurement as in a kilogram of CFCs a day. Other patterns are num years old to refer to age, as in Eve was around two years old; and times in expressions of comparison, e.g. ten times fresher, three times the size of Britain.
Chapter 4. Time nouns
There are also examples where a formal pattern is less obvious, but it is clear from the context how time is used to measure something: (5) A DAD who tried to rob a village shop using a Toilet Duck lavatory cleaner had his jail term cut from three to two years yesterday. (6) In sum, money is to be made in short-dated stock – up to five years – unless . . .
Investing time The functional units of the group investing time are combinations of a verb and a time noun that express how time is used for a specific purpose or in a specific way. A detailed account of this group will be given below.
Time passes The functional group that is characterised by the meaning time passes contains examples which share the meaning of time as something that passes independently and cannot be manipulated. In contrast to this, the previous meaning group saw time in relation to someone who uses it and/or in relation to something that requires time. Now, it is the passing of time that affects other actions or situations. Thus it is possible to regard something as a waste of time or as an opportunity to buy someone time. Time may pass in a quiet way without disturbance, as in example (14) below, but it may also cause stressful situations when it is running out. The following are the 8 examples collected in the group time passes: (7) Magda we can’t; we’ll lose time. (8) French officials are scornful of what one senior diplomat calls a “complete waste of time”. (9) But you’ll be wasting your time. (10) From the moment the drama began to unfold, Ashdown and Wilson knew that the press-gagging injunctions they secured last weekend could only buy them time to plan their DLE. (11) . . . that, at least, gave us time to think. (12) And the Bald Eagle, 58, reckons time is running out for clubs like Derby to win top honours.
English General Nouns
(13) But despite the last-minute reprieve, time is running out for America’s Death Row prisoners. (14) Though the day had passed off peacefully in St Etienne, . . .
History, life The next functional group is labelled history, life because its examples refer to time as a period in people’s lives. As regards the way in which time is related to people, different points of view are possible. The period of time may be related to an individual person, e.g. Ruud Gullit’s unlamented time, or the point of view may be that of society, e.g. times of recession, or even history, as in the following example: (15) In Christian times these feasts were replaced by Candlemas and by the festival of St Brigit, daughter of a Druid, Mary of the Gael and fostermother of Jesus, who kept the flame of Celtic tradition burning at Kildare.
What all of the examples have in common is that the period of time is specified by contextual elements. A variety of modifiers allows for flexibility within the meaning of the history, life group: (16) there’s a few golden years left, you see . . . (17) . . . even though he admits there were times he felt like giving up. (18) He knows these are dangerous times we live in.
Contextual clues may also be found in larger stretches of context: (19) NO MATTER what you do, how hard you try, there may be times when your child behaves appallingly. Managing these times so that your child’s behaviour improves can be difficult and stressful, but . . .
And there are more fixed patterns, as in Tesco have kept up with the times in financial products where times refers to modern times.
School, university The examples of this group are restricted to year and years and contain forms such as the first years, the sixth-year master, that are used in the context of school or university.
Chapter 4. Time nouns
Evaluation and text organisation The group evaluation and text organisation is more complex than the previous functional categories, and its definition depends on features that are illustrated by the other groups. Thus its discussion will be postponed to Section 4.4.
Combinations The group combinations is less a functional group in the above sense than a collection of examples for which the similarity is primarily formal. It contains combinations of nouns, or nouns and adjectives, e.g. lunch times, time limit, fiscal year, new year’s resolution. Other examples of combinations are hyphenated forms such as opening-day, half-time, 23-year-old. Combinations may function as nouns, but they can also be similar to other word classes, e.g. a two-year contract, an injury-time equaliser, where the combination functions as an adjective, or working full time where it is an adverb. This group is not discussed in detail, although it plays a role in the discussion of year and years in Section 4.6, and the formal similarities of the examples also hint at functional similarities that could form starting-points for future work.
Other examples The category other contains examples that do not occur often enough for the definition of a functional group. Additionally, it includes examples with a meaning that is less assimilable within the broad time meaning shared by the other functional groups, e.g. at the end of the day occurs four times with a nontemporal meaning that can be used to introduce a conclusion. Such examples could also be considered as borderline cases, and it may be argued that at the end of the day should be treated in a similar way to at the same time in the time orientation group, which also includes examples where the temporal aspect is used as a means of text organisation. Further cases of the group other are unclear examples, examples which have been assigned the wrong tag, names, and fairly idiosyncratic uses as in Toshiba Year of Invention awards. Some combinations are fairly similar to such cases of the category other, e.g. Boxing Day, Easter Day could be regarded as names, but they were treated as combinations because they are less specific than the names of products such as Avon Hydrofirming Day Lotion. Finally, examples are also classified as other when they illustrate features specific to newspaper style, e.g. in headlines and/or sports reports:
English General Nouns
(20) 1 Leading Article: Jack Straw gets tough on crime – But duff on the causes of crime. Time for a rethink? (21) Fans bury Bankies; Division Two; Full Time; Football; Match report (22) Smith’s pay day
Milk Race winner Chris Lillywhite repaid his debt to team-mate Brian Smith as the Isle of Man-based Scot is third-time lucky in the Manx International . . .
To exclude such examples is not unproblematic, since headlines are an important feature of the news reporting genre, and genre characteristics affect the uses in all examples. The exclusion of these examples was a purely pragmatic decision, in order to avoid too many individual cases within the broader functional groups. It has to be noted, however, that within the scope of a larger study, the occurrence of general nouns in headlines could turn out to be an important aspect of their behaviour. On the whole, the category other would yield further classifications if more data was analysed. However, within the scope of the present study, pragmatic decisions were necessary to enable a reasonable overview of first results in the nature of an exploratory study. Frequency differences may be interesting points for further study, but in the present study the numbers are too small for precise interpretation, and only tendencies will be considered in the present chapter. In the time orientation group, we find examples of all the nouns. Time orientation is the largest group for all the nouns. There are other groups, e.g. school, university, which are not relevant to all the nouns. In the following three sections, I will look at the groups time orientation, investing time, and evaluation and text organisation in more detail. The time orientation group contains the largest number of examples. The investing time group illustrates important aspects of time nouns in verb patterns, and the evaluation and text organisation group illustrates features that play a part in all the time nouns. Thus the three functional groups can be taken as illustrative of the main points that characterise the examples of time nouns in the present study. The functional groups hint at many other features of time nouns, and parallels to other uses of time nouns (which are not attested in the small number of concordance lines) can be easily identified, but the focus of the present study is on those points that are indicated by the data under investigation.
Chapter 4. Time nouns
. Time orientation For all the nouns, a large number of examples belong to the functional group time orientation. Some of the examples occur repeatedly, e.g. all the time, at all times, this year, over the years, every day. Other types of repetition allow for some variation in form, e.g. for (two/three/. . .) years; and there are examples that occur just once, e.g. to this day, time and time again. Nevertheless, all of these examples are similar, in that they express some kind of time orientation in the text. The time orientation can focus on different aspects of time: e.g. on that day marks a point in time, over the past two years refers to a period of time, and every day expresses repetition. What is essential to time orientation is the link to the context. The phrasal unit By the time the bell rang for the end of the lesson is an example of a link to the textual context that has two directions of orientation. The ringing of the bell marks a point in time, and the by includes the period of time up to this point. Thus the time expression is linked both to the clause following it and to the story as it has developed in the preceding text. An example of a link to the broader context is last year. When this time expression occurs in a text, we do not automatically find an explicit date in the same text to make the meaning of last clear. The reference point for this time expression may be found in the broader context of situation. This first overview presents units of time orientation as a fairly heterogeneous group. Tendencies of structural patterning are easier to see when the nouns are dealt with individually. The 44 examples of time are shown in Concordance 4.1 below, with the examples sorted alphabetically by the first word to the left of the node word time: Concordance 4.1 The 44 examples of time in the time orientation group per cent rise in labour costs at a veloping a socialist legality at a cted by the subjects.
Time and ions have to be a good bet, at any ne drunk who would fall over every h President Gaviria. Its the first r of us say anything and the first owards Spain. For almost the first ng the Wisden Trophy for the first I admitted to myself for the first t doesn’t mean we can’t shock from ’s frantic efforts to backpedal in on why you shouldn’t recover it in the point: revelation must come in r goblins or elves. Suppose a long ppier now than you have for a long
time when industrial production rose onl time when it had not yet been possible t time again we’ve been told it would pose time. But I prefer to start the ball rol time the train lurched to a stop and eve time a Chilean head of state has visited time I heard it I had tears running down time in memory, the election turned not time since that Illingworth-inspired tr time that there were strong resemblances time to time.”
As for dropping any h time to make the save. Although the home time. Meanwhile, you can remind each oth time, and liquid assets are worth more time ago they had to hide underground be time fate may even link you with an old
English General Nouns
elephone and said, ‘Hey, you, next bodyguards, and you’d be in in no aughs> start a row no ids are affecting your uterus over ms, losing her appeal. At the same rmed once and for all. At the same ivalent of an MoT.
At the same dy’s moving their head at the same himself against Hibs for a SECOND o master the task in such a short rnment’s education policy for some dea to hold a summer fete and that epend on the whole package at the cting my own film, Orphans, at the ts, it is also frightening. At the . That’s what producers do all the dmits: ‘I felt like dying all the talk about it and watch it all the p on our mobile phone bill all the rough edges wore off.” And all the ts chief executive puts it, by the terrific,” said Anastasia. ‘By the ckroom for other textbooks. By the VISIT ANY university city at this ir cerulean blue trumpets. At this ‘Don’t move, I mean business this class, you name it. I think this lash with Australia in five weeks
time you see me I’m going to be standing time.
It makes me suspect that they time at all. But he’s time. As I’ve explained, diagnostic pro time we have seen the elevation of my o time, the surrogate mother herself is u time, pressure to improve standards cam time. Now this time I want you to keep time tonight. The last time the teams me time. Bear in mind I was there for a wee time, but his resignation letter to his time we raised £88 for Acorns. Two time. In a near one-hour speech to the time. Ken and Paul came down on set and time British Bio had discovered that on time and usually it comes from outside time over the cocaine business. It was time. I used to leave the room when she time. He has threatened to leave me a f time I was thinking, ‘You’re a smelly o time of its results on 10 September. Le time I’m sixteen I # Tsar!” interrupted time the bell rang for the end of the l time of year and you will hear a tinklin time of year, many small greenhouses are time # She ordered him to strip naked t time I have achieved an almost distilled time.
Larder said: ‘We play far too
Most of the units are repeated, either in identical form, as in at the same time, or with some variation, e.g. in the examples with first time. Forms that occur only once in the above set of examples, e.g. in five weeks time, still seem familiar enough, so that we may expect that a larger amount of data will yield repetitions of these forms as well. Although more data will contain other units that occur just once, because of the high frequency of time nouns we can assume that an extensive study will produce a set of groups with similar meanings and functions. The evidence of the present study already indicates early tendencies. We see that in examples such as all the time, at all times, at times, the forms time and times are used in a more universal way, in contrast to patterns of year, years and day that are better suited for precise measuring of time as in a year earlier, two years ago, the day before. So it is not surprising that the plural form years, for instance, shows a tendency for patterns that refer to precise periods of time, e.g. for two/three. . . years, whereas patterns of the plural form times tend to be associated with frequency and repetition rather than periods of time, e.g. three/several/many times. In addition to numbers and other indications of measurements, e.g. long, short, many, etc., we find elements such as for, first, next, last, ago, and before
Chapter 4. Time nouns
that can be considered as ‘linking elements’, since they signal how the time expressions depend on the context to establish the time orientation. Such elements play an important role in the comparison of time expressions, and in the distinctions of patterns and meanings. A typical pattern of the singular form year, for instance, is last year. With the plural form years, however, last is less frequent and does not immediately precede the noun, but occurs in the examples The last few years, the last five years. The concept of ‘linking elements’ could also lead to an improved account of words whose grammatical status has always been a matter of discussion. Looking at ago, for instance, Hoey (2004a: 387) points to the difficulty of finding a convincing grammatical account of this word. As a linking element, ago is viewed as part of patterns of time orientation. A point for further studies is the investigation of time expressions that occur in the same text. In the discussion of textual primings, Hoey (2004a: 403ff.) illustrates, for instance, the occurrence of years in cohesive chains. An interesting question will be to find out more about how different time expressions as they are described in the present study are related across texts and how their contexts are linked and shade into each other. The occurrence of time expressions across texts can be interpreted as co-occurrence patterns which are not limited to a context of few words, but span larger contexts across a text. In this sense time expressions can give a text cohesion. The present study focuses on the narrow context of time nouns. The narrow context is interpreted as an indication of the textual function ‘time orientation’. Without further distinctions according to the type of contexts to which the expressions link, there is more room for describing similarities that cut across syntactic classifications. For instance, although most of the time units function as adverbials in the clause, time expressions are also found as modifiers in noun phrases, as in the following example: Absolute power for 15 years has corrupted absolutely. The functional group of time orientation does not distinguish between these uses, but focuses on the similarities that characterise the units. Another example of the functional interpretation being differently detailed than a syntactic analysis is provided by examples such as after tea on the second day, by January this year. These sequences are simply treated as a single functional unit expressing time orientation, without considering questions of whether after tea and on the second day, or by January and this year are two time adverbials in a sequence (cf. e.g. Biber et al. 1999: 816f.). Furthermore, there are cases in which a functional interpretation is even in conflict with a syntactic interpretation. Take for instance the unit at any time of the year. Syntactically, the noun year is part of the modifier of time. This view assumes a
English General Nouns
hierarchical structure of the noun phrase giving priority to time as the head of the phrase. However, as a time expression, the function of the nouns seems to be better described as depending on the combination of the two of them. In Section 4.6 an example will be given where the noun following of may even be considered to be the notional head of the phrase. The advantage of the functional approach is that it is more open to finding similarities between the uses of time nouns. Such similarities are less obvious when syntactic distinctions are applied early in a classification of examples. The group investing time (cf. 4.3) is further evidence of the need for open categories of interpretation. The differences between a functional and a syntactic approach to time nouns illustrate differences between a top-down versus a bottom-up approach to grammar. In syntax, functional interpretations focus on clause elements, with the result that lexical items tend to be treated as realisations of higher level functional categories. From a syntactic point of view, most examples in the time orientation group are parts of adverbials. However, adverbials can be realised in various ways. According to Biber et al. (1999: 768), prepositional phrases are the most common syntactic realisation of adverbials, followed in frequency by adverbs, and noun phrases are among the realisations that are comparatively rare (prepositional phrases are 10 times more frequent than noun phrases). Concentrating on time adverbials, the picture changes slightly (cf. Biber et al. 1999: 787): although prepositional phrases and adverbs are still the most frequent groups, the difference in frequency with noun phrases decreases (of time adverbials about 30 per cent tend to be realised as prepositional phrases and about 20 per cent as noun phrases). Nevertheless, the nouns that function as adverbials do not receive much attention. Apart from frequency, another reason why nouns in adverbials may not play an important part in syntactic descriptions is the complementary treatment of characterising subject and object. Subjects and objects are often realised by noun phrases, so in this case the nouns have a central role and figure prominently in grammatical desriptions. On the whole, this syntactic interpretation makes time nouns unlikely candidates to illustrate typical noun functions, but leads to terms such as ‘quasi-grammatical’ to describe their use.
Chapter 4. Time nouns
. Investing time The following instances were classified as examples of investing time:
Concordance 4.2 The 15 examples in the investing time group o jobs. Shouldn’t he be devoting his cerely felt that they needed to give nutes from the end, Fulham still had and had to tell him they didn’t have ati rice, and if you do not have the RS, if I read them aright, have much nc with an age which can’t spare the of an American who has spent a long en round the world. I spent a lot of unger brother who spent such a short thday to tell me he was spending the ises of VR, it will take a very long en here was the place that took five ad its teething troubles too, taking intment that the bank would take two
time to one or the other to make sure time and effort to themselves only. W time to miss more openings. Bracewell time to chat to him. So he just walke time or inclination to soak and slowl time for politics or politicians. If time and is anyway too impatient for time abroad. Her delivery is dramatic time in Edinburgh.” Having just finis time in Hong Kong that he hardly spea day with another friend. I felt as if time to deliver - a matter of decades, years to gentrify to industrialised c years to shed the mocking nickname of years to recoup its initial 400
The broad meaning shared by these examples is that time can be used for something, or invested in something. More specific meanings depend on details of the core pattern V . . . time noun . . . For instance, in combinations with take, the pattern take . . . time noun to-inf indicates that the action involved needs time to complete. The verb spend can be used to express the place where someone uses their time: in Edinburgh, abroad, or the manner in which they use their time: with another friend. Although the present study is only based on a few examples, it seems that each of the verbs shown above (devote, give, have, spare, spend, take) will have specific patterns that are associated with the meaning of the verb in the investing time group. On the basis of 1000 concordance lines of time, Mahlberg (forthcoming, b) provides a more detailed discussion of subgroups of investing time patterns. The association between meanings and patterns is the central point of the Pattern Grammar. However, the definition of the investing time group is based on an approach that is different from that of Hunston & Francis (2000). The Pattern Grammar accounts for generalisations, but the use of word classes also limits the type of comparison that is possible across patterns. This limitation becomes particularly obvious in the division of the two Grammar Pattern volumes into verbs on the one hand, and nouns and adjectives on the other. Hunston & Francis (2000: 35) admit that this division “has the disadvantage of obscuring relations between patterns”, which they illustrate with examples of introductory it patterns: It hurts me to think of that
English General Nouns
and It would be a shame to lose touch perform similar functions, but the first pattern, it V n to-inf, is listed as a verb pattern, whereas the second pattern, it v-link N to-inf, is a noun pattern. For the investing time group, it is not primarily the distinction of word classes, but the generalisations within each class that make the similarities between the patterns difficult to see: different types of verb patterns are involved within the same meaning. Patterns of devote such as Shouldn’t he be devoting his time to one or the other are covered by V n to n (Francis et al. 1996: 426), whereas he was spending the day with another friend illustrates the pattern V n prep (Francis et al. 1996: 322). Even the notional groups of the Grammar Patterns, i.e. the groups that collect different patterns with similar meanings (cf. Section 2.3.2), do not bring the above patterns of spend and devote together. There is a notional group “Beginning, continuing, and ending: events, periods of time” (Francis et al. 1996: 616), which contains examples such as A lot of time was spent talking on the phone, but the above examples of spend and devote are not covered by this notional group. Instead, the pattern V n adj, for instance, as in Shares ended the day slightly higher, is accounted for by the same notional group. The Pattern Grammar distinctions result from its aim of finding generalisations and giving a comprehensive account of the main verb patterns. Generalisations leading to the definition of functional groups focus on smaller sets of lexical items, and can thus give more emphasis to similarities in meaning. Furthermore, in the functional groups, the time nouns – not verbs – are the starting-point that leads to the identification of verb patterns. With the focus on the nouns, it is also possible to describe evaluative features of the investing time patterns. The take patterns, for instance, stress that the action involved is something demanding, which needs a lot of time. This aspect can be made explicit in the time expression e.g. take a very long time, taking years. It can also be related to the type of action, as in here was the place that took five years to gentrify to industrialised country status where to gentrify to industrialised country status is something that does not happen overnight. Elements of the context may also stress the effort that is required, e.g. Still, CNN, the BBC’s principal rival, had its teething troubles too, taking years to shed the mocking nickname of ‘Chicken Noodle News”, where teething troubles contributes to the prosody of difficulty. Another example of evaluation involves the units neg have time to/for, spare the time for, which express the idea that an action or activity is not important or interesting enough to someone to use their time for it. For instance, they didn’t have time to chat to him. The evaluative aspects of the time meaning that play a role in these examples will be discussed in more detail in the following section.
Chapter 4. Time nouns
Although the functional group investing time illustrates differences between the present approach and that of Hunston & Francis (2000), the investing time group is in keeping with the Pattern Grammar in the sense that it does not require syntactic distinctions. The question of whether a verb is followed by an adverbial or an object is not involved when describing surface patterns of verbs. Furthermore, the pattern approach does not assign examples such as those of take and spend an exceptional status as “more idiomatic” expressions (cf. 4.1). Still, the present generalisations are not as broad as in the Pattern Grammar, and functional similarities between the verbs are central to the definition of the group. These functional similarities also play a part in relation to the other functional groups of time nouns (cf. 4.5).
. Evaluation and text organisation Evaluation and text organisation are functions that are not specific to time nouns only, but can be found in many different forms, sometimes spanning fairly large amounts of contexts. Terminology in the area of evaluation studies varies, and it seems that the object of study is difficult to grasp. Chapter 6 will deal in more detail with evaluation. For the discussion in the present section, the central point is the social dimension of evaluation. Parameters of evaluation are defined by the value system of a society, which is reflected in language use. Crucial to the functional group evaluation and text organisation is the importance of time in people’s lives, a point that plays a role in all of the categories discussed in the present chapter. Time is so fundamental to our lives that we continually relate to it. All of the functional groups that are outlined in Section 4.1 illustrate different facets of the importance of time which are interrelated: time passes; time can be measured or serve as a measurement; people organise their lives with regard to time, and have to decide what they do with their time; actions or situations can be judged according to their duration or the moment when they take place; time is regarded as something valuable that can be lost, wasted or devoted to something, but cannot be controlled or restored once it has run out. The present group of examples differs from the first six groups, as the evaluative function or the text organisation function seem to be more central to the examples. The examples of the present group are mainly of three types. The first type are examples of time that express the notion that something should be done or that the situation is appropriate for a particular action. The following examples are found with this meaning:
English General Nouns
(23) It is time they were filled out. (24) It’s time for us to act. (25) Could it be that Armani thinks the time has come for a business realignment? (26) Even with the war over, it was no time to be clever.
In the second group of examples, year or day are used to evaluate something, by giving it a special role within a period of time. The nouns occur with an of -construction, as in the best buy of the past year, a further burning issue of the day. But also genitive constructions are possible Especially good for this year’s fresh, demi-sheen look. The last group are examples of the type years of and day that/when. For the noun years, the examples of years of could be characterised as descriptions of a quality of time. The quality of time is specified by what follows of, e.g. years of smoking, years of big surpluses in the social-security system. The evaluative element of years of may be seen in its ability to add weight to the negative aspect of something by stressing its duration, e.g. the 25 years of shit I’ve put up with. The effect to which years of contributes is related to other elements in the context, e.g. in a region which endured years of suppression both endure and suppression contribute to a negative air that is supported by years of. Other uses of the unit years of are, for instance, its occurrence in expressions of time orientation, e.g. during Lesley’s years of living above Leigh’s restaurant in Notting Hill Gate. As its function varies with its context, years of is regarded in the first place as a unit that introduces a quality of time, and then it is further interpreted so that instances of this unit may belong to the category evaluation and text organisation. The units day that/when mark a specific day. Among the functions of this unit is its ability to introduce a temporal clause, e.g. The day I visited, the set was devoted to a scene featuring Dorothea. In such examples, the day is used in a way similar to the conjunction when, but day can give more emphasis to the specific occasion when something happened, and may in this sense be regarded as a means of text organisation. A point about the complexity of the evaluation and text organisation group is that these two functions are closely related. They focus on different aspects of the same phenomenon. Evaluating something is a judgement of goodness, for instance, or of the importance of the evaluated entity (cf. Chapter 6). The identification of evaluation in text depends on the way in which information is presented, i.e. the way in which the text is organised. If we approach the functions from a more abstract point of view, a separation may be easier.
Chapter 4. Time nouns
We could concentrate on a few fairly straightforward types of realisation: structures expressing that X is Y (cf. Chapter 6), whereas adverbials such as firstly, then, particularly could serve as examples of text organising devices. In a text, however, the functions are interdependent. For the examples of the present functional group, evaluative functions and functions of text organisation seem to be a central aspect of their uses in texts. In contrast, for some of the examples of the other groups the evaluative aspect is less central, e.g. the group school, university, where year in the sense of ‘school year’ or ‘year at the university’ can be primarily regarded as a special type of measurement. The examples are a reflection of a social value system, where successful education plays an important role, but the group school, university is a more marginal functional group. The broad meaning of time as something that passes and is valuable captures the relationships between the other groups in a more obvious way reflected by the patterns. That time is valuable also becomes obvious by the parallels of using spend both with time and with money, and sometimes we even say that time is money. The metaphorical concept ‘time is money’ has received much attention in cognitive linguistics. In Lakoff & Johnson (1980: 8) we find, for instance, the following examples illustrating this metaphor [my italics]: (27) I don’t have the time to give to you. (28) How do you spend your time these days? (29) I’ve invested a lot of time in her. (30) I don’t have enough time to spare for that.
All these examples would be classified as investing time in the present framework. Other examples from Lakoff & Johnson (1980: 7f.) are: (31) I lost a lot of time when I got sick. (32) You are running out of time.
These examples would belong to the functional group time passes. This group stresses that time is beyond human control. It cannot be manipulated, so a situation can become very stressful when time is running out, or some illness may cause a loss of time which cannot be avoided by holding back the clock. The present view of the evaluative aspects of time in relation to money differs from a cognitive approach in that it is not explanatory: time is not perceived as something valuable because of its relationship to money, the relationship lies in the shared patterns. In contrast, Lakoff & Johnson (1980) claim that:
English General Nouns
Corresponding to the fact that we act as if time is a valuable commodity – a limited resource, even money – we conceive of time that way. [. . .] we are using our everyday experiences with money, limited resources, and valuable commodities to conceptualize time. (Lakoff & Johnson 1980: 8f.)
On the basis of the corpus data, the statement is weaker: time and money are observed to have similar meanings and occur in similar patterns.2 In Section 2.4.1 it is argued that the object of study of a corpus theoretical approach is language as documented in corpora. On the basis of the data, observations are made that describe meanings. No claim is made about explanations for processes of the brain. However, the evidence from corpora may be used in other linguistic disciplines for further interpretations, but the corpus theoretical approach does not claim to explain mental processes such as conceptualisation. Corpus data may be taken as evidence on the basis of which assumptions can be made about cognitive and psychological aspects of the creation of meaning. The theory of lexical priming (cf. Section 2.3.3) links corpus linguistic and psycholinguistic arguments, and the effects of frequency play a part if meanings are interpreted in terms of primings: the primings of a word are shaped by the encounters that language users have with the word. With the ‘From-Corpus-To-Cognition Principle’ Schmid (2000: 39) explicitly relates frequency to arguments of cognitive linguistics: “[f]requency in text instantiates entrenchment in the cognitive system”. It seems undeniable that frequency of use plays some part in our knowledge of meanings of words. This seems to be particularly the case for the semantic prosody of an item, as the semantic prosody is realised in the contexts of words and is dependent on recurrent uses (cf. Sinclair forthcoming). On the basis of the corpus data, a question that could be raised about the ‘time is money’ metaphor relates to the directionality of the arguments. Time is the most frequent noun in two large general purpose corpora. The patterns that are described above do not occur only with time but also with other time nouns, and also with nouns that refer to time but are not discussed in the present study, e.g. spend/invest weeks, months, ages, etc. Furthermore, the arguments put forward for the category time passes seem to remain convincing without relating them to arguments of time and money. Thus it may be that the influence of money on the evaluative meaning of time is not as strong as the metaphor explanation seems to claim. What ultimately happens in the brain is not for a corpus theoretical approach to discuss. What we can say, however, is that time and money share patterns of use which reflect similarities in meaning:
Chapter 4. Time nouns
both nouns refer to valuable resources. The metaphorical explanation may be a reflection of the fact that prosodies are meanings hidden from our intuition.
. The fuzziness of meaning The above discussion illustrates that meaning is difficult to describe. Even if we try to relate a description of meaning to surface patterns that are visible in the corpus, any type of categories will have fuzzy boundaries, and their descriptions will involve some subjectivity. For the functional groups of the present chapter, we can argue that sometimes the same example would fit equally well into several categories, as different points of view are possible on the same situation. For the sake of simplicity, the decision to create a separate category was made, based on a comparison with the other examples. The fairly heterogeneous labels of the functional groups are indicative of the relative nature of meaning. The labels would become more homogeneous if each was a nominal expression, e.g. instead of time passes the group could be called time development, and instead of investing time we could have time investment, which would be more similar in form to time orientation. However, such formal similarities would make it more difficult to see functional distinctions. The label investing time, for instance, indicates that time is used for a specific purpose or in a deliberate way, while time passes is meant to stress the independence of time. The labels cannot be as iconic as Hunston & Francis’ (2000) coding of patterns, as the functional groups associate meanings with more than one structure. Even though the labels cannot be unambiguous, they can still be more suggestive than abstract and formally similar expressions. The variation that characterises the functional groups illustrates that the description of the time nouns operates at different levels of context. While the group investing time deals with verb patterns that contain time nouns, the group time orientation covers noun phrases, prepositional phrases and even clauses introduced by a time noun. The functional similarities within a group depend to some extent on lexical elements of the context, e.g. linking elements such as last, next in expressions of time orientation. Again, the lexical elements that characterise a functional group may cut across structural categories so that, for instance, in the group time passes we find nominal expressions (a waste of time) along with verb structures (lose time). The contextual relations become even more complex with the groups evaluation and text organisation and school, university. Here the text, and even the social context, is important,
English General Nouns
which results in an increase in structural variations for the local context. More data would be needed to bring out the tendencies more clearly. Because of the flowing boundaries between the categories, detailed quantitative information plays a minor role in describing the functional groups. The focus of the study is qualitative, and is applied to the nature of the contextual relations in the first place. However, further studies may bring to light interesting facts by following quantitative details of the tendencies that are suggested by the present analysis. What becomes clear even from the preliminary quantitative results is that all the nouns presented in this chapter have a single meaning – their time meaning – that is most frequent; and for all the nouns, time orientation makes up a fairly large part of this most frequent meaning. This broad ‘time’ meaning refers to the relations between the nouns and represents a comparative point of view. In the description of the time meaning, the overlap of the functional groups illustrates a general point about meaning. Because of its contextdependency, meaning is always relative, and thus has to be described in relation to other meanings. But we can take at least two approaches to the description of meaning of lexical items. On the one hand, we can focus on a single item and add information about the context to reduce ambiguity. On the other hand, we can focus on similarities of meaning across lexical items, so that facets of a broader meaning become discernible through the comparison of different examples. The time meaning, of which the functional groups highlight different facets, is an example of such a broad meaning. Although the lexical items that are compared are not described in full detail, the description illustrates that they share aspects of meanings. The description of shared meanings is more detailed than a Pattern Grammar description. The features that the lexical items share are part of the semantic prosodies of the individual lexical items. Semantic prosodies account for evaluative and pragmatic features of meaning (cf. Section 2.3.1, also Stubbs 2001a: 65f.). According to Sinclair (1996) the semantic prosody has a leading role to play in the integration of an item with its surroundings. It expresses something close to the “function” of the item – it shows how the rest of the item is to be interpreted functionally. (Sinclair 1996: 87f.)
Semantic prosodies are realised in a variety of contexts. In this sense, the textual patterns of the time nouns may be interpreted as ways of realising aspects of the prosodies of the time meaning, which in turn depends on the type of texts which form the basis for the interpretation. The texts reflect the value system of the social discourse community.
Chapter 4. Time nouns
. The need for local categories of description The variety of factors involved in the description of time nouns is a consequence of the lexical point of view. The analysis starts from the word, and compares the contexts in which it is found. Thus, words are not seen as realisations of structures on a higher level, but are instead the basis for generalisations leading to descriptive categories. The generalisations summarise the behaviour of similar examples. It is as such a summarisation that the labels of the functional groups have to be understood. Because of the multifunctionality of words that makes language such a powerful tool, a bottom-up description is bound to yield fuzzy categories. If words are linked to other words, these links cannot be one-dimensional. Thus, different interpretations of the same sequence of words are possible. The present description focuses on lexical items, but it is not an extended dictionary entry for each of the nouns. Similarities between the nouns play a part in the functional categories, with the result that the functional groups are generalisations: for an individual noun, meaning distinctions become apparent through comparison with other nouns. It is this comparison that enables the generalisations, which build up a grammatical description that is lexical in nature. It is also this comparison that compensates for the limited number of examples that could be dealt with in the present study. Looking back at Table 4.1 we see that for the noun day there are two meanings that are each represented by only a single example. For day there is one example in the group investing time: he was spending the day with another friend. And there is one example in the group time passes: the day had passed off peacefully in St Etienne. Thus, focusing on day only, the more general features of these meanings would figure less clearly than by comparing them to examples of time and years. And even if many more examples of day had been analysed it is not clear that something like an investing time, or a time passes group would have emerged, for two main reasons: firstly, corpus linguistic methodology seems to suggest that in the description of individual words frequent meanings deserve more attention, a practice that is also applied in dictionaries that organise meanings in frequency order. So a detailed study of day will probably be very informative with regard to different types of time orientation or combinations (e.g. fourday week, two day visit) as the two biggest groups illustrated in Table 4.1 are likely to make up a high proportion in a larger set of examples, too. Secondly, more examples of the same word will result in the repetition of formally similar patterns of this specific word. So even if we find more instances of spend the day the meaning features of the investing time group that have been discussed
English General Nouns
in Section 4.3 would continue to depend on the comparison of examples of time, years and day. With the help of comparisons the present study aims to account for both lexical features and generalisations across lexical items which contribute to a grammatical description. In Section 3.3.2 the concept of local grammar was introduced. Descriptive categories of a local grammar are more flexible than categories that involve a fairly high degree of abstraction. Compared to the categories of syntax, the distinctions made in the present chapter give more emphasis to words functioning in units in texts than to hierarchical distinctions, as they characterise phrases in clause elements. The units of time orientation in particular illustrate that the meaning depends on the unit as a whole, and not primarily on the noun. Furthermore, examples of time nouns show that a syntactic analysis of the noun phrase (in terms of head and modifier) may even run contrary to the way in which meaning is created in the text. An example is the unit years of, which functions as an introductory element for a quality of time. A syntactic analysis would regard the of-phrase as the modifier of the head years, but in the text the element following of appears to be the notional head. This situation not only depends on years but is also part of the use of of, as Sinclair (1991: 81ff.) illustrates. Another difference from the standard syntactic interpretation is the distinction between singular and plural that is relevant to time nouns. When time nouns express time orientation, they do not affect number choices in the verb, and the effects on determining elements are also more limited, as the focus is on the time expression as a unit. It is sufficient to see all the time, by the time, at a time when. . . as functional units, without deciding whether time is countable or uncountable. Moreover, number distinctions seem to imply that singular and plural forms of the same noun have a very similar meaning. If we take year, for instance, and look at its meaning without reference to a context, it can be described as ‘a period of twelve months’, and the distinction between singular and plural is straightforward. In context, however, the forms of the nouns are less similar. The singular examples fall into two large groups: time orientation, with 47 examples, and combinations, with 39 examples. In contrast, the largest group of the plural forms is time orientation (with 69 examples), and combinations do not occur. The combinations of the singular form are mainly num-year-old or num-year forms. Thus the singular form, as well as the plural form, combines with numbers greater than 1. It is arguable whether year in these forms should still be regarded as a noun, or the whole form be treated as an adjective. If we decide to see the whole form as an adjective, its adjective use is restricted. The form tends to occur as a premodifier in the noun phrase, as
Chapter 4. Time nouns
in example (33) below, whereas predicative constructions that express a similar meaning are formed with old in combination with years as in example (34). (33) The 21-year-old factory worker bombarded his ex-girlfriend . . . (34) Eve was around two years old when I brought hear here . . .
Thus, if we look at meaning in context, distinctions between singular and plural forms become much more meaningful than may be obvious for the word in isolation. The present approach is based on arguments that are similar to those of Hunston & Francis (2000), but the local categories also suggest alternatives to some of the Pattern Grammar distinctions. Both approaches stress the relationship between form and meaning, and show that pattern descriptions can have advantages over syntactic distinctions. An important example is the functional group investing time. The verbal units that were identified in this group avoid ambiguities of syntax by treating the time nouns as part of the verb patterns. The Pattern Grammar uses similar arguments to completely abandon the syntactic distinctions of clause elements. As we saw in Section 2.3.2, for the verb patterns that Hunston & Francis (2000: 151ff.) analyse, the argument is convincing and some of the issues that they raise also play a part in Biber et al. (1999: 403ff.) when suggestions for multi-word verbs are discussed.3 Still, the Pattern Grammar does not provide alternatives for all of the distinctions that clause elements can describe. Hunston & Francis’ (2000) emphasis on verb patterns easily covers obligatory adverbials and those ambiguous cases where it is difficult to distinguish between adverbial and object. The description of time nouns, however, shows that adverbials which are optional in structural terms also play an important role in text. Such features cannot be revealed by the pattern approach, as they are not linked closely enough to verbs. When Hunston & Francis (2000) illustrate how texts can be analysed in terms of patterns, cases such as the following occur in the examples (Hunston & Francis 2000: 219): (35) A friend of mine told me this amazing story the other day. N . . . of . . n | V. . n . . . . . . . . . . . . . . . . . n |
The example is part of a longer stretch of text that is analysed in terms of patterns. Without going into details about the pattern representation in the line below the sentence, the example clearly illustrates that optional time adverbials are not seen as central to the texts, and are not considered in the textual analysis (cf. also e.g. Hunston & Francis 2000: 206).
English General Nouns
Furthermore, in the characterisation of noun patterns, the characteristics of time nouns cannot be made manifest either. The type of generalisations made in the Pattern Grammar are based on broad word-class patterns; thus they are bound to have a levelling out effect on the features that are relevant to the present study and in the Grammar Patterns; meaning relations, as they are described in the time group, are difficult to trace. Take the noun time, for example. As time can occur in a number of different patterns the index of the Grammar Patterns refers to 23 pages that contain pattern information for time. One of the groups in which time occurs in the Grammar Patterns is called the ‘TIME’ GROUP, which has the pattern at N and contains nouns referring to times, as in the following examples (Francis et al. 1998: 268): (36) The survey, taken at the beginning of this month, showed that 90 per cent expect Labour to form the next government. (37) At Christmas the shops are decorated exquisitively. (38) They wrote her a formal letter, asking her to call at the sheriff ’s office at her convenience. (39) The players get up at dawn to train five times a week. (40) At the time of his death he was working on ‘Hot Photography’, a book about film and cameras in tropical climates.
Another group in which we find the noun time is characterised by the pattern v-link adj N to-inf which is shared by nouns such as decision, habit, mistake, moment, person, and place. Examples are (Francis et al. 1998: 120): (41) Now is a good time to buy a classic car. (42) It was a hard decision to make. (43) It’s a good habit to get into.
Although such pattern information provides valuable insights into meaning relations, the wealth of information makes it difficult to focus on particular features. As the patterns of the Pattern Grammar are described in terms of word classes, sequences such as last year or next year are more difficult to find. The noun year is listed, for instance, with the pattern ord N. The pattern ord N describes nouns that are preceded by an ‘ordinal’: an ordinal number such as first, second, third, or an adjective such as next, last, final (Francis et al. 1998: 106). The meaning of year that is assigned to this pattern, however, is illustrated by the following example (Francis et al. 1998: 108): (44) They’re always swearing and saying they’ll beat up little first years.
Chapter 4. Time nouns
The pattern last year is not seen as sufficiently typical to be accounted for in the Grammar Patterns. But it is such collocations that characterise the time nouns in units of time orientation. The present approach does not adopt a quantitative approach to collocations, but illustrates collocational patterns by comparison of the nouns in the functional groups. Hunston & Francis (2000: 234) stress the quantitative features of the description of collocations, and argue that such quantification is difficult within the Pattern Grammar framework, as there is “a multitude of different levels of significance” (Hunston & Francis 2000: 234) and a decision to prioritise ‘strong’ collocates would require binary choices which are incompatible with the concept of co-selection. Co-selection is not a matter of all or nothing, but a matter of degree.4 The argument in Chapter 3 that explains the method of the present study runs along similar lines. However, by focusing on a group of nouns, collocations can be approached from a comparative point of view, which refers to the functions of lexical items in texts. For instance, in the example of day that has been discussed above, the cooccurrence with spend receives more attention by comparing it with spend time. Similarly, the sequence of the year is more clearly recognised as having an evaluative function by comparing it to of the day (cf. also Chapter 6). The concept of linking elements that has been introduced in Section 4.2 offers one possibility for summarising functional types of collocations. Thus finer distinctions on the continuum of co-selection can become visible.
Conclusion The present chapter suggests a functional description of the time nouns that distinguishes aspects of a broad ‘time’ meaning shared by the nouns. It has become obvious that syntactic and functional units are not necessarily the same, and hierarchical distinctions as they are made in syntax are not always appropriate to a textual interpretation. Such conclusions are possible if we accept that meaning is relative. Reference points vary with the lexical item, as well as with the items that form the basis for comparison. It is argued that patterns play an important role in the characterisation of time nouns, but a Pattern Grammar approach would still not provide sufficient information. The functional groups suggest how to complement both the picture of the Pattern Grammar and syntactic analyses: the functional groups illustrate local textual patterns. Features of text are part of the meanings of lexical items. To make such meanings visible, descriptive categories of a local nature are necessary. They are defined by comparing lexical items. The labels of the functional groups provide a summary
English General Nouns
of functional similarities. Local textual functions of time nouns are visible in a narrow context, which sometimes leads to interpretations of expressions as ‘idiomatic’ or ‘quasi-grammatical’. Such a point of view, however, is a simplification of the textual dimension. The time nouns illustrate that part of the textual meaning is a reflection of the value system of a social discourse community. To give substance to the argument, the evaluative interpretation has to be tied to surface features: the local textual patterns. The description of time nouns shows that our corpus-driven investigation of general nouns has taken a completely different path from what may have been expected on the basis of Halliday & Hasan’s (1976) arguments and examples. Chapter 7 will return to the question of how the two approaches are related.
Notes . The markup for headlines is not necessarily consistent throughout the corpus. . Cf. also Sinclair’s (1996: 84) interpretation of naked eye, where he warns of ‘obvious’ metaphorical extension: “it is dangerously easy to reverse the procedure and assume that the metaphorical extension is obvious”. In the field of Discourse Analysis, too, it has been stressed that ultimately it will be the situation of use that determines interpretations of figurative meanings, cf. Norrick (2001: 87f.). . For a further discussion of patterns and syntactic analyses see Muhkerjee (2005) on V n n patterns. . However, in the discussion of the example according to rumours Hunston & Francis (2000: 206) point out that “those parts of the text that show little pattern dependency do depend to a large extent on the co-occurrence of significant collocations”.
Appendix 100 concordance lines for time e
r cent rise in labour costs at a time when industrial production rose veloping a socialist legality at a time when it had not yet been possible as taken English football to an all-time low. You only have to look back a ected by the subjects.
Time and time again we’ve been told it would po sions have to be a good bet, at any time. But I prefer to start the ball r was born. He was living on borrowed time.’ And you just withdrew the loan. er-Mycal, a company owned partly by Time Warner and partly by Nichii, the reparation time: 20 minutes Cooking time: 8-10 minutes KEBABS 800g monkfis - But duff on the causes of crime. Time for a rethink? NO we did not in sales over Christmas - a crucial time in the games business. Shareholde one drunk who would fall over every time the train lurched to a stop and e
Chapter 4. Time nouns
stuta pen 6, Zanetti 45 After extra time; Argentina win 4-3 on penalties A feguard Roddy Black netted an extra-time winner to rescue Brechin’s Scott owards Spain. For almost the first time in memory, the election turned n ing the Wisden Trophy for the first time since that Illingworth-inspired t h President Gaviria. Its the first time a Chilean head of state has visit admitted to myself for the first time that there were strong resemblanc er of us say anything and the first time I heard it I had tears running do thin contemporary performance. Fool Time, Britainnia Road, Kingswood, Bris third week you get that much free time whenever you want it. The software it doesn’t mean we can’t shock from time to time."
As for dropping any s bury Bankies; Division Two; Full Time; Football; Match report
Magda we can’t; we’ll lose time."
You can," Alison said. ‘A if I read them aright, have much time for politics or politicians. If a task I really enjoy so I take my time. Before I start, I take the butter lephone and said, ‘Hey, you, next time you see me I’m going to be standing bodyguards, and you’d be in in no time.
It makes me suspect that they Even with the war over, it was no time to be clever. Surreys with fringes laughs> start a row no time at all. But he’s one moment of non-space and non-time, became non-matter and non-energy, diplomat calls a ‘complete waste of time".
President Chirac of France round the world. I spent a lot of time in Edinburgh." Having just finished t great social gatherings of our time." sure they’re social," says ids are affecting your uterus over time. As I’ve explained, diagnostic orchestra evolved from being a part-time, small-scale, regional orchestra to Why is it the case that taking part-time work is made so difficult by the And the Bald Eagle, 58, reckons time is running out for clubs like Derb t despite the last-minute reprieve, time is running out for America’s Death tinues today through racism. It’s time for us to act."
Rigoberta that state norgal time in norgal’s time. Er and they can without the use o ems, losing her appeal. At the same time we have seen the elevation of my o irmed once and for all. At the same time, the surrogate mother herself is uivalent of an MoT.
At the same time, pressure to improve standards cam dy’s moving their head at the same time. Now this time I want you to keep imself against Hibs for a SECOND time tonight. The last time the teams m
English General Nouns
o master the task in such a short ger brother who spent such a short ernment’s education policy for some ea to hold a summer fete and that its chief executive puts it, by the pend on the whole package at the That’s what producers do all the ecting my own film, Orphans, at the with an age which can’t spare the nts, it is also frightening. At the uld not exclude claims outside the rice, and if you do not have the uld it be that Armani thinks the admits: ‘I felt like dying all the alk about it and watch it all the up on our mobile phone bill all the rough edges wore off." And all the a concise social history of the terrific," said Anastasia. ‘By the kroom for other textbooks. By the too comfortable."
When the know it gives us a flavour of the last weekend could only buy them VISIT ANY university city at this class, you name it. I think this ‘Don’t move, I mean business this eir cerulean blue trumpets. At this II won the gold medal with a total erhouse that will prove unbeatable. s ago. In Ruud Gullit’s unlamented position: that, at least, gave us clash with Australia in five weeks f> But you’ll be wasting your as different things demand er your
time. Bear in mind I was there for a we time in Hong Kong that he hardly speaks time, but his resignation letter to his time we raised £88 for Acorns. Tw time of its results on 10 September. time. In a near one-hour speech to the time and usually it comes from outside time. Ken and Paul came down on set and time and is anyway too impatient for su time British Bio had discovered that on time limit.
Tony Baker, deputy time or inclination to soak and slowly time has come for a business realignmen time over the cocaine business. It was a time. I used to leave the room when she time. He has threatened to leave me a fe time I was thinking, ‘You’re a smelly ol time. When Blake was born (1757) it was time I’m sixteen I # Tsar!" interrupted time the bell rang for the end of the time comes, Nicholas Boyle will time doesn’t it. <M02> time to plan their DLE.
They did the time of year and you will hear a tinklin time I have achieved an almost distilled time # She ordered him to strip naked th time of year, many small greenhouses are time of 3min 27.78sec, while Sean Olsso Time Warner, previously considered the time, this match would not have been los time to think.
Leaving one boat time.
Larder said: ‘We play far too time. You know what Mary’s trying to do, time and attention at different times.
100 concordance lines for times p; Stoughton on March 2 at 10. Times readers can buy it for 9 t d intricate plotting made it seem 10 times fresher than Hollywood thrillers fulfilment but trades on a p/e of 13 times -- N Brown shares are worth ret even though ARM is now valued at 21-times last year’s revenues, experts a ile second-degree relatives are 1.3 times more likely to develop it. These sed inks. Dimensions (W,D,B.) 35 × 23 × 56cms.
