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1 Until the phenomena of any branch of knowledge have been submitted to measurement and number, it cannot assume the dignity of a science. (Sir Francis Galton, ) 1

2 _ Contents Acknoledgements. 5 List of Abbreviations. 6 Part I History, Criteria and Research 1 Introduction. 8 2 History of Corpora Early Corpus Linguistics The Chomskyian Revolution Modern Corpus Linguistics Corpus-Based Research Definitions Some Arguments in Favour of Corpus-Based Research Corpus Outline and Creation Synchronic Corpus Design Criteria Diachronic Corpus Design Criteria Kinds of Corpora Tools for Corpus Exploitation Concordancers Frequency Tables Taggers Parsers Ready-Available Tools versus Own Programming Corpus Networks 56 2

3 Contents Part II Applications 4 Applications of Corpora The Use of Corpora in Linguistics Corpora and Grammar Corpora and Lexicography/Terminology Corpora and Morphology Corpora and Semantics Corpora and Pragmatics Corpora, Stylistics and Discourse Studies Corpora, Language Teaching and Learning Corpora and Ethnolinguistics The Use of Corpora in Translation Parallel, Multilingual and Comparable Corpora Machine Translation Translation Memory Systems Corpora vs. Termbanks Translation Teaching and Translation Research Thinking Globally - Acting Locally Critical Comments Conclusions Case Study The Problem Formulation of the Hypothesis Selecting the Corpus Choosing the Tools Summarising the Restrictions The Study Synonymy Cacophony Conclusions Part III Conclusion and outlook 6 Drawing Conclusions

4 Contents _ Appendices 1 Glossary Major Corpora Available Software Available for Corpus-Based Research Results of a Collocation Search of Tra and Fra 135 Bibliography Index

5 Acknowledgements I am particularly grateful to my parents, who have been an invaluable support throughout all these years of "foreignness" in Graz. Above all, I would like to thank my supervisor, Dr. Ursula Stachl-Peier. Ursula, thank you for being not only a brilliant linguist, but also a wonderful friend, and for having made this thesis less inadequate than it still remains. This thesis reflects the precious work and committment of numerous corpus researchers throughout the years. It is thanks to these far-sighted linguists that we are nowadays faced with the expanding universe of corpus studies. It is to them that I shall dedicate this work of mine. 5

6 List of Abbreviations AI Artificial intelligence ARCHER American Representative Corpus of Historical English Registers BNC British National Corpus Brown Brown Corpus of Standard Written American English CALL Computer-assisted language learning CAT Computer-aided translation CRATER Corpus Resources and Terminology Extraction CSAE Corpus of Spoken American English GPEC Guangzhou Petroleum English Corpus ICAME International Computer Archive of Modern English ICE International Corpus of English ICLE International Corpus of Learner English Lancaster/IBM Lancaster/IBM Spoken English Corpus LIP Lessico di frequenza dell'italiano parlato LLC London-Lund Corpus LOB Lancaster-Oslo/Bergen Corpus LSP Language for specific purposes MT Machine translation OCP Oxford Concordancing Program POS part-of-speech SEC IBM-Lancaster Spoken English Corpus SEU Survey of English Usage Corpus 6

7 PART I HISTORY, CRITERIA AND RESEARCH 7

8 1 Introduction Over the last 40 years linguistic research has undergone major changes. While many have deplored this, arguing that it has led to a lack of focus and to inconsistency, others (i.e. Svartvik 1990) have pointed out that it has greatly contributed to academic cross-fertilisation and the development of new approaches, which will hopefully help us to better understand the intricacies of human language processing. In the wake of the new insights associated with the 1950s and Chomsky, new ways of analysing language were pioneered, while older approaches were virtually abandoned. Among those dismissed as unscientific or inappropriate was also the corpus-based approach to language which up to then had been the main way of gathering language data. Corpus linguistics, as this discipline is generally called, became neglected, but it by no means disappeared. Nowadays, the usefulness of corpora 1 is being rediscovered and they are proving an excellent resource for a wide range of research tasks, not only because they give evidence of current language usage, but also because they permit us to compare synchronic and diachronic shifts within a language and so become the foundation of analysis. 1 The word corpus derives from Latin and means body, a body of texts. Any collection of more than one text can therefore be defines as a corpus, which seems a simple enough notion. In linguistics, however, it is slightly more complicated, as various criteria of inclusion have to be taken into consideration when a corpus is compiled (see Section 3.1). 8

9 Introduction One of the aims of my thesis is to provide an overview of the many possible applications that corpora can have in language and translation studies. When I set out to write this thesis I also had another goal in mind - a slightly subtler one. What I wanted to do was to help bring about a change in well-established views of the role of teachers and learners. Nowadays students are more and more often asked to organise and manage their own learning, they are given freedom of choice about which subjects to study, but most of the time they are not told how to go about it. The teacher is no longer the sole provider of knowledge, and s/he often falls victim to sheer economic constraints. This new setting turns out to be a very big challenge, a challenge to the student and the teacher alike. I strongly believe that a corpus-based approach to language and translation teaching is a tool which will allow us to keep up with the times as it ensures easy and immediate access to empirical language data. Students are encouraged to deduce rules from naturally occurring evidence and no longer solely rely on introspection-derived data, be they those presented by their teachers or themselves. This thesis includes three main sections. After a short introduction, Part one, Chapter 2 deals with the history of linguistic research based on corpus evidence, from the early 1950s to the Chomskyian revolution until today. Chapter 3 discusses the main elements of corpus-based research, exploring issues like corpus outline, corpus creation, the different kinds of corpora, the tools needed to exploit a corpus, finally focusing on the possibility of establishing a computer network for corpora studies. Part two Chapter 4 places the emphasis on the numerous applications of corpusbased research, discussing both possible areas of research in linguistics and translation studies. The case study (Chapter 5) - which completes Part Two - introduces an example of corpus exploitation which might be of relevance to linguists as well as to translators. 9

10 Introduction Conclusions are then drawn in Part Three. Section 6.1 suggests possible topics for further research for translation students, while Section 6.2 focuses on teaching corpora and describes course design issues. This thesis aims to be above all a basic introduction to corpus-based research for (translation) students and teachers with no or very limited knowledge of the area. The focus is on possible applications in a variety of domains, including grammar, lexicography, morphology, semantics, pragmatics, stylistics, ethnolinguistics and language teaching. It is hoped that by showing the potential of corpus-based research, more teachers and students will be motivated to try out similar studies themselves. The same intention guides the Case Study, which tries to show very faithfully the kind of problems that may emerge during a project, and where solutions might be found. It will not discuss in any detail the more technical, computational issues, such as quantitative data analysis, factor analysis, multidimensional scaling, cluster analysis or chi-square tests. Suggestions for further reading on these subjects are included in most of the standard books on computational linguistics (i.e. McEnery (1992), Souter and Atwell (1993)). 10

11 2 History of Corpora The main aim of Chapter 2 is to give a brief overview of the history of evidence-based language analysis. 2 I shall first describe early approaches to corpus linguistics, and then - in Section focus on Noam Chomsky, who is arguably the most influential person in 20 th century linguistics. I shall discuss his objections to corpus linguistics and arguments in favour of rationalism. In 2.3 I shall concentrate on more recent trends in linguistics and the revival of corpus linguistics as one of the most valid tools for language modelling. 2.1 Early Corpus Linguistics Early Corpus Linguistics is not a canonised definition of a fixed period of time. The term was first used by McEnery (1996) to define all work carried out in the various areas of linguistics before the methodology advocated by Noam Chomsky became predominant. Corpus linguistics has actually been mainstream for a long time, although it was initially discussed under a variety of names and labels. Different branches of linguistics, such as field linguistics and the post- Bloomfieldian structuralist tradition 3 of Harris and Hill, based their studies on a methodology which nowadays might very well be called corpusbased. 2 The information included in this Chapter is based on accounts in several textbooks and on internet sites (Chomsky 1957, 1962, 1965; Cravetto et al. 1997; McEnery and Wilson 1996 as well as Exact page references are only given when I quote directly from a source. 3 See Appendix 1. 11

12 History of Corpora In the 1950s then, Chomsky brought about a revolution which favoured an approach which was based on data derived from native speaker introspection and totally excluded corpus evidence. As we will see later in this chapter, his doctrine put a spoke in the still fragile wheel of corpus linguistics. Before the 1950s several corpus-based studies had been carried out, not only in the field of language acquisition - maybe the most obvious application of corpus-based research -, but also in the area of language pedagogy (Fries and Traver 1940), spelling conventions (Käding 1897), comparative linguistics (Eaton 1940), syntax (Fries 1952), semantics (Lorge 1949) and lexis (Gougenheim et al. 1956). Language acquisition studies first applied the methodology of corpus-based description in the first half of the 20 th century. Research focused on child language on the basis of parental diaries recording dialogues and utterances. Generally, however, these were simply a collection of transcribed interactions which rarely complied with even the basic principles of corpus studies, i.e. representativeness. This material was still being used in the late 1970s by Chomskyians as a source of normative data, which in fact made this field of research one of the few areas that successfully continued throughout the Chomsky-dominated period and so represented a continuum in corpus linguistics. It also laid the foundations for a new generation of corpus linguists like Svartvik and Leech, whose early career was in language acquisition before they started to apply corpus-based methodologies to other domains. Corpus evidence in order to establish spelling conventions was first used by Käding in 1897, when he put together an impressive 11-millionword corpus of German texts to analyse and correlate the frequency of letters and letter sequences in the German language (for details see Käding 1897). Comparative linguists also included corpora in their studies. One of them was Eaton, who in 1940 compared the frequency of word meanings in German, Italian, French and Dutch. The exploitation of the corpus 12

13 History of Corpora allowed him to derive useful information about semantic links across languages and communication situations. The modernity of such a study is proved by the fact that only in the second half of the 1990s McEnery and Oakes were able to create a corpus which was large enough to produce similar results (McEnery and Wilson 1996:3). Arguably the two most important early fields of application of corpus studies are syntax and semantics. In 1952 Fries created a corpus of transcribed telephone conversations which he then transformed into a descriptive grammar of English. His pioneering work provided a model for the one developed by Quirk et al. in 1985, more than 30 years later (see Fries 1952). Semantic studies were carried out also for other European languages. French was analysed in detail by Gougenheim et al. (1956), who transcribed a corpus of spoken language gathered from 275 informants with the aim of describing high frequency lexical and grammatical choices (for further details see McEnery and Wilson 1996:4). 2.2 The Chomskyian Revolution Between 1957 and 1965 Noam Chomsky published three books which brought about a radical change in linguistics (see Chomsky 1957, 1962, 1965). Chomsky s criticism of behaviourist approaches 4 initiated a new kind of research which was founded on rationalism and focused on introspective judgement rather than external data analysis. Introspection, Chomskyians argued, was quicker and more reliable (for further comments see In some ways, Chomsky s success was also the result of a certain degree of arrogance on the part of early computer linguists who believed that corpora were collections of all potential utterances. They consequently argued that corpora were the only valid method of describing language and therefore its primary explicandum (Leech 1991:8). 13

14 History of Corpora Chomsky strongly objected to this view of language as a finite medium. He pointed out that language structures vary in line with personal style preferences, generic constraints or in response to contextual (situational) needs, that neologisms are constantly added to enrich the lexis of languages and meanings also change. Corpora - which are finite, and according to Chomsky skewed therefore were unsuitable as models for language: Any natural corpus will be skewed. Some sentences won t occur because they are obvious, others because they are false, still others because they are impolite. The corpus, if natural, will be so wildly skewed that the description [based upon it] would be no more than a mere list. (Chomsky 1962:159) One of the main tenets of Chomsky was that linguistic theories should be cognitively plausible and able to simulate and recreate natural language processing. Chomsky therefore stressed the need for new analytical tools, which - he argued would have to focus on competence instead of performance (Chomsky 1962). Competence is introspection. Introspection is the knowledge of a language that we derive from our own experience. Chomsky did not actually deny the importance of performance, but he was convinced that it was competence that both explains and characterises a language. For his language model Chomsky therefore discarded performance data, as these were considered to be too weak to mirror the linguistic behaviour of a language community, and were influenced by too many language-independent factors, including physical shape of the speaker, his/her moral principles, etc One of the major drawbacks I see in Chomsky s approach is that language rules risk to become (or remain) the domain of influence of those in power. Despite Chomsky s professed reluctance to prescribe and repeated claims in all Generative Grammar influenced textbooks that all the versions produced by native speakers are equally acceptable, 4 See Appendix 1. 14

15 History of Corpora decisions on what standard language is continue to be the prerogative of the educated elite. Another critical issue in Chomsky s theory, I believe, is his assertion that only data derived through introspection will not be skewed. To me, introspection-based data are themselves a kind of evidence and equally skewed because no native speaker will ever produce the full range of utterances possible in a language. They may perhaps be a weaker variation of empiricism, as we do not yet have a methodology available to retrieve and classify uniformly such personal references. Another point is that introspection, although it can be recorded, is often left unspoken. Recordings can easily be analysed, yet thought processes remain unobservable because they cannot be shared with other people. Corpus evidence, on the other hand, is publicly available and can therefore be commented on by all. Even if we try to ignore the fact that any kind of recording is a corpus, it can still be argued that modelling and - as a direct consequence - identifying the rules of the language used by a certain language community must be an endeavour shared by the entire community and not only an effort engaged in by a linguistic enclave. Again, this touches on linguistic empowerment. Competence and performance recognise in their conceptions of language analysis different linguistic leaders. While introspection focuses on the individual, trying to provide him/her with the necessary tools for language analysis, corpus linguistics makes use of already existing tools to draw conclusions from naturally occurring data. The Chomskyian revolution had far-reaching consequences, not simply in linguistics. His emphasis on cognitive plausibility encouraged computational linguistics to build systems which would simulate human intelligence and carry out intelligent tasks. 2.3 Modern Corpus Linguistics 15

16 History of Corpora Despite Chomsky s success, corpus-based work continued throughout the 1950s and 1960s, especially in those fields where introspection failed to achieve satisfactory results. Phonetics and language acquisition were a case in point. It suddenly became obvious that introspection - especially in child language acquisition - can only be applied once metalinguistic awareness has been developed, in other words we can apply competence to language modelling only when we are aware of being linguistically competent. Different corpus linguistics projects were started. Between 1959 and 1961 Randolph Quirk began working on his Survey of English Usage (SEU) Corpus. Very shortly afterwards Nelson Francis and Henry Kuçera from Brown University in Providence (Rhode Island, United States) set out to put together the Brown Corpus, a sample of printed American English, which is still considered the standard reference for language enquiries. In 1975 Jan Svartvik and his team at Lund University began to transcribe - and so to render machine-readable - the spoken part of the SEU corpus. The advent of the computerised corpus, that is a collection of machinereadable texts, is indeed a major turning point in corpus linguistics. The availability of institutional and private computing facilities fuelled the growth of corpora, which from 1965 onwards started to became bigger and bigger in size and number: the largest corpus available nowadays is the Bank of English corpus, a monitor corpus created at the University of Birmingham in collaboration with Collins COBUILD, which includes more than 200 million words of British English and is constantly been added to. In recent years, a new trend has started which promises exciting new opportunities. Corpus researchers like McEnery and Wilson have realised that artificial data - collected via introspection - can have a place in corpus linguistics, albeit with the proviso that corpus evidence will act as a control, a yardstick (1996:16). Corpus linguistics - as McEnery and Wilson (ibid.) put it - should be a synthesis of introspection and 16

17 History of Corpora performance analysis, a mix of artificial and natural observation. Fillmore sums up this symbiosis very well: I don t think there can be any corpora, however large, that contain information about all of the areas of English lexicon and grammar that I want to explore [but] every corpus I have had the chance to examine, however small, has taught me facts I couldn t imagine finding out any other way. My conclusion is that the two types of linguists need one another. (Fillmore 1992:35) 17

18 3 Corpus-Based Research This Chapter focuses on corpus-based research and provides a more detailed description of the methodologies used. Section 3.1 gives a definition of corpus and corpus-based research ; in Section 3.2 I shall outline some of the strengths of a corpus-based approach which have been cited in the literature to prove its validity. Before giving a detailed description of the different kinds of corpora in Section 3.4, I shall delineate in Section 3.3 the main points to be considered when building a corpus. The tools needed for corpus exploitation are explored in Section 3.5, while Section 3.6 outlines criteria for building a computerised infrastructure for corpus-based work. 3.1 Definitions In Chapter 1 I already defined a corpus as any collection of more than one text. In modern linguistics, however, this collection of texts must fulfil certain criteria to be considered a corpus. As stated by McEnery and Wilson (1996:21), a corpus must display four main features: representativeness finite size machine-readable form be a standard reference. Representativeness 18

19 Corpus-Based Research Representativeness is a major point. There are basically two ways of collecting data: either you record every single utterance of a specific language variety, or you build a sample of the entire population of texts that you want to analyse. As already pointed out in Chapter 2, a living language constantly grows and changes, which means that its lexical and syntactic structures are in theory infinite. The first approach is therefore impossible to implement. Generally, therefore, corpus linguists will opt for the second methodology. However, sampling also has its pitfalls (see Noam Chomsky s criticism of corpora being skewed in previous chapter). When compiling a corpus, we are influenced by many factors (i.e. availability in electronic form, easy retrieval, ready-made text collections, etc.) that automatically - and, sometimes, unconsciously determine the range of texts from which the corpus will be sampled. Representativeness therefore can never be totally objective. While this may be a major drawback, I believe, sampling is still a legitimate approach, provided we are aware that samples can never reproduce a language variety completely accurately and faithfully, and provided we ensure that the collected corpus is balanced. Biber (1993b) has outlined a number of steps to produce an appropriately balanced corpus: before starting to build a corpus, clearly state the aim of the study, specify the linguistic variety to be analysed, and indicate what he (ibid.:243) calls the sampling frame - the entire population of texts from which samples are taken. Samples must average out and provide a reasonably accurate picture of the entire language population. Finite Size The second feature mentioned is the size of the corpus, which should be finite. Not all corpora are finite, however: monitor corpora, such as John Sinclair s Bank of English, are open-ended collections. Texts are constantly added to the corpus in order to update the material already 19

20 Corpus-Based Research collected and so produce reasonably exhaustive samples of language use. Determining the size of a corpus is one of the most difficult tasks in corpus creation. In order to facilitate this task, computational linguists have elaborated algorithms which are able to approximately quantify variables such as chance and significance. 5 When the total number of words is reached, collection stops and the corpus is thereafter not increased in size. Apart from monitor corpora, the only exception to this principle is represented by the London-Lund Corpus (LLC), which was enlarged in the mid-1970s by Sidney Greenbaum in order to cover a wider variety of genres. Machine-Readable Form A corpus also has to be available in machine-readable form. As we saw in chapter two, an essential difference between early and modern corpus linguistics is the ready availability of microcomputers. Before the advent of computerised data processing, corpus exploitation was a very long, expensive and error-prone procedure: just think of Käding s 11-millionword corpus and the 5,000 Prussian analysts he needed to go through the corpus. Svartvik was one of the first linguists that applied the principle of machine-readability to data collection by phonetically transcribing the spoken texts of Quirk s SEU. Incidentally, the LLC is one of the few corpora still available in book format. Although machine-readability is nowadays to be considered as absolutely necessary, there are still some exceptions that need to be mentioned. A complete concordance of the Lancaster-Oslo/Bergen Corpus (LOB) is available only on microfiche, while some other spoken corpora such as the Lancaster/IBM Spoken English Corpus offer copies taped for phonetic analysis. The advantages of machine-readable corpora can therefore be summed up under the following 3 main headings: 20

21 Corpus-Based Research thanks to corpus exploitation tools - i.e. concordancers, frequency listers, parsers - data can be searched and manipulated easily and time-effectively, and so simplify result analysis; they can easily be enriched by adding information about grammar and lexis 6 ; they can be made available to researchers within a couple of minutes via Internet connections. Standard Reference The fourth requirement is that a corpus should also be a standard reference. Sharing a collection of texts with the rest of the research community can make out of an appropriately designed corpus a yardstick for language modelling, which can then also be used for later research projects. A further advantage is that by using a single source of linguistic information it is easier to compare different studies, because the opinions expressed can be judged exclusively on the basis of the claims made by the scholar who carried out of the analysis. 3.2 Some Arguments in Favour of Corpus-Based Research The literature cites numerous arguments in favour of corpus-based research. The perhaps greatest advantage of corpus linguistics over other approaches that I can see is that corpus linguistics is not restricted either to theory or just to practice, but that it combines both. It makes available the methodology that is required to carry out studies into language usage, but not without also insisting that the empirical data are included in an overall theoretical description. In the following, I shall quote a few more arguments that have been used in favour of corpus studies. 5 For further reading on quantitative data analysis see McEnery and Wilson 1996, pp For further information about corpus annotation see tagged corpora (Chapter 3 Section 4). 21

22 Corpus-Based Research Corpus-based studies vs. introspection-derived data First and maybe most importantly, a corpus-based approach provides naturally recorded, linguistically comprehensive examples. We often explain a phenomenon or a grammar rule by means of introspectively created examples. Although we are convinced of their validity, we have to admit that frequently the examples we produce are either clichés or rather idiosyncratic. Evidently, we need proof from natural language use: in grammar teaching there is no point in analysing a language variety that either does not exist in reality, or is considered a sort of sublanguage used by a closed circle of language users (i.e. prototypical examples used during a language learning class). If we use a corpus, then this corpus might of course also contain such prototypical or idiosyncratic examples, but, because of the greater representativeness of the corpus, these examples form part of the knowledge of a wider linguistic community, and therefore must be accepted as commonly shared rules. Corpora as Material for Inductive Learning 7 Possibly the biggest advantage of the corpus-based approach is that it allows inductive learning and is always learner-centered. In the final analysis it is the learner that decides what s/he wants to focus on, what s/he wants to learn, how s/he wants to acquire knowledge or skills and at which pace. The learner can therefore exploit the corpus for his/her own purposes, which may indeed vary between learners. (Incidentally, corpora have also been successfully used in teacher training; see Renouf 1997). Corpora and Reusability Another important characteristic of the corpus-based approach is the reusability of linguistic resources. We have already mentioned among the four main features of a corpus that it is a standard reference. Public 22

23 Corpus-Based Research availability and source reusability are, in my opinion, closely linked. Together they assure coherence, a much appreciated quality in linguistics. A coherent approach to language study permits project comparison and contributes to a global analysis of language use. Corpora and Interdisciplinarity Closely linked to the issue of reusability is the issue of interdisciplinarity. Various linguistic fields can all exploit the same corpus to conduct stylistic, syntactical and lexical studies. The results can then be used as the basis of cross-cultural studies. Corpora and Flexibility Corpora enable all kinds of studies. They can for instance be provided with extra tags which are added after every word to describe its status. This is the so-called annotated corpus, which McEnery and Wilson (1996:24) call a repository of linguistic information, because it makes explicit what in the plain text was still implicit (for further details see Section 3.4). Corpora and Negative Results Another major advantage of corpus analyses is that even a negative result is an analysable result. Corpora and Specificity Yet another advantage of a corpus-based approach is its specificity: the choice of texts to be included in the corpus and the design criteria applied can reflect a specific attitude to language analysis, which means that we can modify not only the methodology, but also the goal. Different languages or language varieties require different analytical standards or approaches. The corpus can be built in respect of these standards and 7 The various possibilities offered (i.e. CALL) will be described in Part Two, Chapter 4, Section 2. 23

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