MULTEXT: Multilingual Text Tools and Corpora

Total Page:16

File Type:pdf, Size:1020Kb

MULTEXT: Multilingual Text Tools and Corpora MULTEXT : Multilingual Text Tools and Corpora Nancy Ide and Jean V6ronis LABORATOIRE PAROLE ET LANGAGE CNRS & Universitd de Provence 29, Avenue Robert Schuman 13621 Aix-en-Provence Cedex 1 (France) e-mail: ide@fraixll .univ-aix. fr, veronis@fraixll .univ-aix. fr Abstract, MULTEXT (Multilingual Text "Fools and nmnipulate and analyse text corpora and to create multi- Corpora) is the largest project funded in the Commission lingual text corpora with structural and linguistic of European Communities Linguistic Research and markt, p. It will attempt to establish conventions for the Engineering Program. The project will contribute to the encoding of such corpora, building on and contributing development of generally usable software tools to to the preliminary recommendations of the relevant manipulate and analyse text corpora and to create multi- international and European standardization initiatives. lingual text corpora with structural and linguistic MULTEXT will also work towards establishing a set of markup. It will attempt to establish conventions for the guidelines for text software development, which will be encoding of such corpora, building on and contributing wklely published in order to enable future development to the preliminary recommendations of the relevant by others. The project consortimn, consisting of eight international and European standardization initiatives. academic and research institutions and six major MULTEXT will also work towards establishing a set of European industrial partners, is committed to make its guidelines for text software development, which will be results, namely corpus, related tools, specifications and widely published in order to enable future development accompanying documentation, freely and publicly by others. All tools and data developed within the project available. will be made freely and publicly available. Keywords. multi-lingual corpora, text markup, text 2. Project Overview software, corpus annotation. At the outset of the project, the consortimn will 1. Introduction undertake to analyse, test and extend the SGML-based recommendations of the TEl on real-size data, and Text-oriented methods and software tools have come to gradually devch)p encoding conventions specifically be of primary interest to the NLP community. However, suited to nmlti-lingual corpora and the needs of NLP and existing tools for natural language processing (NLP) and MT corpus-based researcb. To manipulate large machine translation (MT) corpus-based research are quantities of such texts, the partners will, in collaboration typically embedded in large, non-adaptable systems with the recently established Text Software Initiative which are fundamentally incompatible. Little effort has (TS[), develop conventions fo," tool co,~struction and use been made to develop software standards, and software tbem to build a r:mge of highly language-independent, reusability is virtually non-existent. As a result, there is a atomic and cxtensible software tools. serious lack of generally usable tools to manipulate and analyze text corpora that arc widely available for These specifications will be the basis for thc research, especially for multi-lingual al)plications. development of two major software resources, namely (a) tools for the linguistic annotation of texts (e.g. At the same time, the availability of data is hampered by segmenters, morphological analysers, part of speech a lack of well-established standards for encoding disambiguators, aligners, prosody taggers and post- corpora. Although the Text Encoding Initiativc (TEI) has editing tools), and (b) tools for the exploitation of provided guidelines for text encoding [Sper94], they arc annotated texts (e.g. tools for indexing, search and so far largely untested on real-scale data, especially retrieval, statistics). This software will be implemented multi-lingual data. Further, the TEl Guidelines offer a under UNIX, while its specific properties should broad range of text encoding solutions serving a w~riety facilitate portability to other systems. Moreover, it will of disciplines and applications, and are not intended to be integrated by means of a common user interface into a provide specific guidance for the purposes of NLP and text corpus manipulation system expected to provide the MT corpus-based research. basic functionality needed in academic or industrial corpus research. For the overall software design as well MIJLTEXT (Multilingual Text Tools and Corpora) ix a as the development of specific components, MULTEXT recently initiated large-scale project funded under tim will capitalise on the experience and, possibly, Commission of European Communities Linguistic preliminary results achieved in the ALEP project. Research and Engineering Program, which is intended to address these problems. The project will contribute to the By using the emerging software tools, the consortium development of generally usable software tools to plans to produce a substantial multilingual corpus, including parallel texts and spoken data, in six EC 588 languages (English, French, Spanish, German, Italian and program can be de-bundled into its constituent programs, Dutch). The entire corpus will be marked for gross each consisting of small, easily understandable piece of logical and structural features; a subset of the corpus will code. MULTEXT will bundle its tools in a be marked and hand-validated for sentence and sub- comprehensive corpus-handling system, as welt as sentence features, part of speech, alignment of parallel demonstrate their use in several high-level applications, texts, and speech prosody. All markup will have to thus showing different ways in which tim "Legos" can be comply to the TEI-based corpus encoding conventions recombined in specific applications. established within the project. Tim corl)us will also serve as a tcstbed for the project tools and a resource for future • Princil/e 3: OperatotZ~'tream approach tool development and evaluation. MUI.'I'EXT will adopt the operator/stream apl)roach to An application programming iuterfime will facilitate the scfftware design, which has had widespread coupling of the progressively refined software and data implementation and use and is generally accepted in components with several existing langt, age application research and industry. In particular, it has been used systems or prototypes. In particular, the industrial increasingly in computational linguistics applications partners phm to develop extraction software fl)r lexieal (see, for instance, [I,ibe92]). The operator/stream and terminological infornmtion to complement and approach has served as the basis for the UNIX operating improve their Terminology Management, Information system, which as a result provides a ready-made platform R.etrieval or Machine Translation systems. Some effcwt for its implementation. will also be devoted to a prototypical api)lication for In the operator/stream approach, data flows in uni- testing and comparing successive versions of a Machine directional "slreams" between functions. Each of these Translation system. functions is an "operator" that translbrms the data as it passes by. Since everything is understood in terms of 3. Background and approach what goes in and what comes out, the emphasis is on what needs to be done rather than how it is done. "Fhis 3.1. Software Standard enables a focus on overall algorithms rather titan implementation details. Component functions are MULTEXT is strongly committed to "software independent, and at no point are compiled together in a reusability", to avoid the re-inventing of tim wheel and single program. This is a key point, since it means that development of largely incompatible and non-extcnsihle each operator can be implemcnted in a different software that is characteristic of much language-analytic language, developed by different people, tested research in the past three decades. Therefore, the project independently, etc. In addition, new functions can be will establish a software standard for the development of phlgged into the stream as necded, and all ft, nctions are its tools. This will enable these tools to be universally completely re-usable in other contexts. used and extended hy others. • Princil~le 4: [hrique &tta type We outline here the principles (borrowed from [IdeV93a]) nnderlying the MULTEXT approach to Commtmication between programs will be by lneaus Of software design, which enable flexibility, extendability, flat, ]roman readable streams and files, apart from well- and reusability. defined, encapsuhlted binary formats for cases such as speech signal, images, or indexes. The only data type is • Principle 1: lxmguage independence therel'tn'e the stving. There is some overhead in this The first goal is to extend existing mctlmds to otlmr ;.Ipproilch, since conversion froul string to, s'ty, nulnbcr and back is required I()r numbers that are to be European languages. So far, these methods have been manipulated arithmetically, but tim speed and storage applied almost exclusively to English. Therefore, the methods will be adapted to produce language- capacities of present-day machines virtu:ally eliminate this concern. More importantly, the use of string data independent tools, by using an engine-based approach only enables an easy test-modify-test cycle, since the where all hmguage dependent materials arc provided as data. Thus, extension of the tools to cover additional input and outi)ut of any step can be examined and languages will in most cases involve only providing
Recommended publications
  • Construction of English-Bodo Parallel Text
    International Journal on Natural Language Computing (IJNLC) Vol.7, No.5, October 2018 CONSTRUCTION OF ENGLISH -BODO PARALLEL TEXT CORPUS FOR STATISTICAL MACHINE TRANSLATION Saiful Islam 1, Abhijit Paul 2, Bipul Syam Purkayastha 3 and Ismail Hussain 4 1,2,3 Department of Computer Science, Assam University, Silchar, India 4Department of Bodo, Gauhati University, Guwahati, India ABSTRACT Corpus is a large collection of homogeneous and authentic written texts (or speech) of a particular natural language which exists in machine readable form. The scope of the corpus is endless in Computational Linguistics and Natural Language Processing (NLP). Parallel corpus is a very useful resource for most of the applications of NLP, especially for Statistical Machine Translation (SMT). The SMT is the most popular approach of Machine Translation (MT) nowadays and it can produce high quality translation result based on huge amount of aligned parallel text corpora in both the source and target languages. Although Bodo is a recognized natural language of India and co-official languages of Assam, still the machine readable information of Bodo language is very low. Therefore, to expand the computerized information of the language, English to Bodo SMT system has been developed. But this paper mainly focuses on building English-Bodo parallel text corpora to implement the English to Bodo SMT system using Phrase-Based SMT approach. We have designed an E-BPTC (English-Bodo Parallel Text Corpus) creator tool and have been constructed General and Newspaper domains English-Bodo parallel text corpora. Finally, the quality of the constructed parallel text corpora has been tested using two evaluation techniques in the SMT system.
    [Show full text]
  • Usage of IT Terminology in Corpus Linguistics Mavlonova Mavluda Davurovna
    International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8, Issue-7S, May 2019 Usage of IT Terminology in Corpus Linguistics Mavlonova Mavluda Davurovna At this period corpora were used in semantics and related Abstract: Corpus linguistic will be the one of latest and fast field. At this period corpus linguistics was not commonly method for teaching and learning of different languages. used, no computers were used. Corpus linguistic history Proposed article can provide the corpus linguistic introduction were opposed by Noam Chomsky. Now a day’s modern and give the general overview about the linguistic team of corpus. corpus linguistic was formed from English work context and Article described about the corpus, novelties and corpus are associated in the following field. Proposed paper can focus on the now it is used in many other languages. Alongside was using the corpus linguistic in IT field. As from research it is corpus linguistic history and this is considered as obvious that corpora will be used as internet and primary data in methodology [Abdumanapovna, 2018]. A landmark is the field of IT. The method of text corpus is the digestive modern corpus linguistic which was publish by Henry approach which can drive the different set of rules to govern the Kucera. natural language from the text in the particular language, it can Corpus linguistic introduce new methods and techniques explore about languages that how it can inter-related with other. for more complete description of modern languages and Hence the corpus linguistic will be automatically drive from the these also provide opportunities to obtain new result with text sources.
    [Show full text]
  • Enriching an Explanatory Dictionary with Framenet and Propbank Corpus Examples
    Proceedings of eLex 2019 Enriching an Explanatory Dictionary with FrameNet and PropBank Corpus Examples Pēteris Paikens 1, Normunds Grūzītis 2, Laura Rituma 2, Gunta Nešpore 2, Viktors Lipskis 2, Lauma Pretkalniņa2, Andrejs Spektors 2 1 Latvian Information Agency LETA, Marijas street 2, Riga, Latvia 2 Institute of Mathematics and Computer Science, University of Latvia, Raina blvd. 29, Riga, Latvia E-mail: [email protected], [email protected] Abstract This paper describes ongoing work to extend an online dictionary of Latvian – Tezaurs.lv – with representative semantically annotated corpus examples according to the FrameNet and PropBank methodologies and word sense inventories. Tezaurs.lv is one of the largest open lexical resources for Latvian, combining information from more than 300 legacy dictionaries and other sources. The corpus examples are extracted from Latvian FrameNet and PropBank corpora, which are manually annotated parallel subsets of a balanced text corpus of contemporary Latvian. The proposed approach augments traditional lexicographic information with modern cross-lingually interpretable information and enables analysis of word senses from the perspective of frame semantics, which is substantially different from (complementary to) the traditional approach applied in Latvian lexicography. In cases where FrameNet and PropBank corpus evidence aligns well with the word sense split in legacy dictionaries, the frame-semantically annotated corpus examples supplement the word sense information with clarifying usage examples and commonly used semantic valence patterns. However, the annotated corpus examples often provide evidence of a different sense split, which is often more coarse-grained and, thus, may help dictionary users to cluster and comprehend a fine-grained sense split suggested by the legacy sources.
    [Show full text]
  • 20 Toward a Sustainable Handling of Interlinear-Glossed Text in Language Documentation
    Toward a Sustainable Handling of Interlinear-Glossed Text in Language Documentation JOHANN-MATTIS LIST, Max Planck Institute for the Science of Human History, Germany 20 NATHANIEL A. SIMS, The University of California, Santa Barbara, America ROBERT FORKEL, Max Planck Institute for the Science of Human History, Germany While the amount of digitally available data on the worlds’ languages is steadily increasing, with more and more languages being documented, only a small proportion of the language resources produced are sustain- able. Data reuse is often difficult due to idiosyncratic formats and a negligence of standards that couldhelp to increase the comparability of linguistic data. The sustainability problem is nicely reflected in the current practice of handling interlinear-glossed text, one of the crucial resources produced in language documen- tation. Although large collections of glossed texts have been produced so far, the current practice of data handling makes data reuse difficult. In order to address this problem, we propose a first framework forthe computer-assisted, sustainable handling of interlinear-glossed text resources. Building on recent standardiza- tion proposals for word lists and structural datasets, combined with state-of-the-art methods for automated sequence comparison in historical linguistics, we show how our workflow can be used to lift a collection of interlinear-glossed Qiang texts (an endangered language spoken in Sichuan, China), and how the lifted data can assist linguists in their research. CCS Concepts: • Applied computing → Language translation; Additional Key Words and Phrases: Sino-tibetan, interlinear-glossed text, computer-assisted language com- parison, standardization, qiang ACM Reference format: Johann-Mattis List, Nathaniel A.
    [Show full text]
  • Linguistic Annotation of the Digital Papyrological Corpus: Sematia
    Marja Vierros Linguistic Annotation of the Digital Papyrological Corpus: Sematia 1 Introduction: Why to annotate papyri linguistically? Linguists who study historical languages usually find the methods of corpus linguis- tics exceptionally helpful. When the intuitions of native speakers are lacking, as is the case for historical languages, the corpora provide researchers with materials that replaces the intuitions on which the researchers of modern languages can rely. Using large corpora and computers to count and retrieve information also provides empiri- cal back-up from actual language usage. In the case of ancient Greek, the corpus of literary texts (e.g. Thesaurus Linguae Graecae or the Greek and Roman Collection in the Perseus Digital Library) gives information on the Greek language as it was used in lyric poetry, epic, drama, and prose writing; all these literary genres had some artistic aims and therefore do not always describe language as it was used in normal commu- nication. Ancient written texts rarely reflect the everyday language use, let alone speech. However, the corpus of documentary papyri gets close. The writers of the pa- pyri vary between professionally trained scribes and some individuals who had only rudimentary writing skills. The text types also vary from official decrees and orders to small notes and receipts. What they have in common, though, is that they have been written for a specific, current need instead of trying to impress a specific audience. Documentary papyri represent everyday texts, utilitarian prose,1 and in that respect, they provide us a very valuable source of language actually used by common people in everyday circumstances.
    [Show full text]
  • Text and Corpus Analysis: Computer-Assisted Studies of Language and Culture
    © Copyright Michael Stubbs 1996. This is chapter 1 of Text and Corpus Analysis which was published by Blackwell in 1996. TEXT AND CORPUS ANALYSIS: COMPUTER-ASSISTED STUDIES OF LANGUAGE AND CULTURE MICHAEL STUBBS CHAPTER 1. TEXTS AND TEXT TYPES Attested language text duly recorded is in the focus of attention for the linguist. (Firth 1957b: 29.) The main question discussed in this book is as follows: How can an analysis of the patterns of words and grammar in a text contribute to an understanding of the meaning of the text? I discuss traditions of text analysis in (mainly) British linguistics, and computer-assisted methods of text and corpus analysis. And I provide analyses of several shorter and longer texts, and also of patterns of language across millions of words of text corpora. The main emphasis is on the analysis of attested, naturally occurring textual data. An exclusive concentration on the text alone is, however, not an adequate basis for text interpretation, and this introductory chapter discusses the appropriate balance for text analysis, between the text itself and its production and reception. Such analyses of attested texts are important for both practical and theoretical reasons, and the main reasons can be easily and briefly stated. First, there are many areas of the everyday world in which the systematic and critical interpretation of texts is an important social skill. One striking example occurs in courtrooms, where very important decisions, by juries as well as lawyers, can depend on such interpretations. Second, much of theoretical linguistics over the past fifty years has been based on the study of isolated sentences.
    [Show full text]
  • Latvian Framenet: Cross-Lingual Issues
    96 Human Language Technologies – The Baltic Perspective K. Muischnek and K. Müürisep (Eds.) © 2018 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/978-1-61499-912-6-96 Latvian FrameNet: Cross-Lingual Issues Gunta NESPORE-Bˇ ERZKALNE¯ 1, Baiba SAULITE¯ and Normunds GRUZ¯ ITIS¯ Institute of Mathematics and Computer Science, University of Latvia Abstract. This paper reports the lessons learned while creating a FrameNet- annotated text corpus of Latvian. This is still an ongoing work, a part of a larger project which aims at the creation of a multilayer text corpus, anchored in cross- lingual state-of-the-art representations: Universal Dependencies (UD), FrameNet and PropBank, as well as Abstract Meaning Representation (AMR). For the FrameNet layer, we use the latest frame inventory of Berkeley FrameNet (BFN v1.7), while the annotation itself is done on top of the underlying UD layer. We strictly follow a corpus-driven approach, meaning that lexical units (LU) in Latvian FrameNet are created only based on the annotated corpus examples. Since we are aiming at a medium-sized still general-purpose corpus, an important aspect that we take into account is the variety and balance of the corpus in terms of genres, do- mains and LUs. We have finished the first phase of the FrameNet corpus annota- tion, and we have collected and discuss cross-lingual issues and their possible so- lutions. The issues are relevant for other languages as well, particularly if the goal is to maintain cross-lingual compatibility via BFN.
    [Show full text]
  • TEI and the Documentation of Mixtepec-Mixtec Jack Bowers
    Language Documentation and Standards in Digital Humanities: TEI and the documentation of Mixtepec-Mixtec Jack Bowers To cite this version: Jack Bowers. Language Documentation and Standards in Digital Humanities: TEI and the documen- tation of Mixtepec-Mixtec. Computation and Language [cs.CL]. École Pratique des Hauts Études, 2020. English. tel-03131936 HAL Id: tel-03131936 https://tel.archives-ouvertes.fr/tel-03131936 Submitted on 4 Feb 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Préparée à l’École Pratique des Hautes Études Language Documentation and Standards in Digital Humanities: TEI and the documentation of Mixtepec-Mixtec Soutenue par Composition du jury : Jack BOWERS Guillaume, JACQUES le 8 octobre 2020 Directeur de Recherche, CNRS Président Alexis, MICHAUD Chargé de Recherche, CNRS Rapporteur École doctorale n° 472 Tomaž, ERJAVEC Senior Researcher, Jožef Stefan Institute Rapporteur École doctorale de l’École Pratique des Hautes Études Enrique, PALANCAR Directeur de Recherche, CNRS Examinateur Karlheinz, MOERTH Senior Researcher, Austrian Center for Digital Humanities Spécialité and Cultural Heritage Examinateur Linguistique Emmanuel, SCHANG Maître de Conférence, Université D’Orléans Examinateur Benoit, SAGOT Chargé de Recherche, Inria Examinateur Laurent, ROMARY Directeur de recherche, Inria Directeur de thèse 1.
    [Show full text]
  • Natural Language Processing, Sentiment Analysis and Clinical Analytics
    Natural Language Processing, Sentiment Analysis and Clinical Analytics Adil Rajput ([email protected]) Assistant Professor, Information System Department, Effat University An Nazlah Al Yamaniyyah, Jeddah 22332, Jeddah, Saudi Arabia Abstract Recent advances in Big Data has prompted health care practitioners to utilize the data available on social media to discern sentiment and emotions’ expression. Health Informatics and Clinical Analytics depend heavily on information gathered from diverse sources. Traditionally, a healthcare practitioner will ask a patient to fill out a questionnaire that will form the basis of diagnosing the medical condition. However, medical practitioners have access to many sources of data including the patients’ writings on various media. Natural Language Processing (NLP) allows researchers to gather such data and analyze it to glean the underlying meaning of such writings. The field of sentiment analysis – applied to many other domains – depend heavily on techniques utilized by NLP. This work will look into various prevalent theories underlying the NLP field and how they can be leveraged to gather users’ sentiments on social media. Such sentiments can be culled over a period of time thus minimizing the errors introduced by data input and other stressors. Furthermore, we look at some applications of sentiment analysis and application of NLP to mental health. The reader will also learn about the NLTK toolkit that implements various NLP theories and how they can make the data scavenging process a lot easier. Keywords: Natural Language Processing (NLP), Data scraping, social media analysis, Sentiment Analysis, Helathcare analytics, Clinical Analytics, Machine Learning, Corpus 1. Introduction The Big Data revolution has changed the way scientists approach problems in almost every (if not all) area of research.
    [Show full text]
  • Improving Statistical Machine Translation Efficiency by Triangulation
    Improving Statistical Machine Translation Efficiency by Triangulation Yu Chen, Andreas Eisele, Martin Kay Saarland University Saarbrucken,¨ Germany {yuchen, eisele, kay}@coli.uni-sb.de Abstract In current phrase-based Statistical Machine Translation systems, more training data is generally better than less. However, a larger data set eventually introduces a larger model that enlarges the search space for the decoder, and consequently requires more time and more resources to translate. This paper describes an attempt to reduce the model size by filtering out the less probable entries based on testing correlation using additional training data in an intermediate third language. The central idea behind the approach is triangulation, the process of incorporating multilingual knowledge in a single system, which eventually utilizes parallel corpora available in more than two languages. We conducted experiments using Europarl corpus to evaluate our approach. The reduction of the model size can be up to 70% while the translation quality is being preserved. 1. Introduction 2. Phrase-based SMT The dominant paradigm in SMT is referred to as phrase- Statistical machine translation (SMT) is now generally based machine translation. The term refers to a sequence of taken to be an enterprise in which machine learning tech- words characterized by its statistical rather then any gram- niques are applied to a bilingual corpus to produce a trans- matical properties. At the center of the process is a phrase lation system entirely automatically. Such a scheme has table, a list of phrases identified in a source sentence to- many potential advantages over earlier systems which re- gether with potential translations.
    [Show full text]
  • Proceedings of the 55Th Annual Meeting of the Association For
    ComputEL-3 Proceedings of the 3rd Workshop on the Use of Computational Methods in the Study of Endangered Languages Volume 1 (Papers) February 26–27, 2019 Honolulu, Hawai‘i, USA Support: c 2019 The Association for Computational Linguistics Order copies of this and other ACL proceedings from: Association for Computational Linguistics (ACL) 209 N. Eighth Street Stroudsburg, PA 18360 USA Tel: +1-570-476-8006 Fax: +1-570-476-0860 [email protected] ISBN 978-1-950737-18-5 ii Preface These proceedings contain the papers presented at the 3rd Workshop on the Use of Computational Methods in the Study of Endangered languages held in Hawai’i at Manoa,¯ February 26–27, 2019. As the name implies, this is the third workshop held on the topic—the first meeting was co-located with the ACL main conference in Baltimore, Maryland in 2014 and the second one in 2017 was co-located with the 5th International Conference on Language Documentation and Conservation (ICLDC) at the University of Hawai‘i at Manoa.¯ The workshop covers a wide range of topics relevant to the study and documentation of endangered languages, ranging from technical papers on working systems and applications, to reports on community activities with supporting computational components. The purpose of the workshop is to bring together computational researchers, documentary linguists, and people involved with community efforts of language documentation and revitalization to take part in both formal and informal exchanges on how to integrate rapidly evolving language processing methods and tools into efforts of language description, documentation, and revitalization. The organizers are pleased with the range of papers, many of which highlight the importance of interdisciplinary work and interaction between the various communities that the workshop is aimed towards.
    [Show full text]
  • Helping Language Learners Get Started with Concordancing
    TESOL International Journal 91 Helping Language Learners Get Started with Concordancing Stephen Jeaco* Xi’an Jiaotong-Liverpool University, China Abstract While studies exploring the overall effectiveness of Data Driven Learning activities have been positive, learner participants often seem to report difculties in deciding what to look up, and how to formulate appropriate queries for a search (Gabel, 2001; Sun, 2003; Yeh, Liou, & Li, 2007). The Prime Machine (Jeaco, 2015) was developed as a concordancing tool to be used specically for looking up, comparing and exploring vocabulary and language patterns for English language teaching and self-tutoring. The design of this concordancer took a pedagogical perspective on the corpus techniques and methods to be used, focusing on English for Academic Purposes and including important software design principles from Computer Aided Language Learning. The software includes a range of search support and display features which try to make the comparison process for exploring specic words and collocations easier. This paper reports on student use of this concordancer, drawing on log data records from mouse clicks and software features as well as questionnaire responses from the participants. Twenty-three undergraduate students from a Sino-British university in China participated in the evaluation. Results from logs of search support features and general use of the software are compared with questionnaire responses from before and after the session. It is believed that The Prime Machine can be a very useful corpus tool which, while simple to operate, provides a wealth of information for language learning. Key words: Concordancer, Data Driven Learning, Lexical Priming, Corpus linguistics.
    [Show full text]