1887
Volume 22, Issue 1
  • ISSN 0929-9971
  • E-ISSN: 1569-9994
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Abstract

One of the most remarkable features of the legal English lexicon is the use of sub-technical vocabulary, that is, words frequently shared by the general and specialised fields which either retain a legal meaning in general English or acquire a specialised one in the legal context. As testing has shown, almost 50% of the terms extracted from an 8.85m word legal corpus, were found amongst the most frequent 2,000 word families of West’s (1953) Coxhead’s (2000) or the (2007), hence the relevance of this type of vocabulary in this English variety. Owing to their peculiar statistical behaviour in both contexts, it is particularly problematic to identify them and measure their termhood based on such parameters as their frequency or distribution in the general and specialised environments. This research proposes a novel termhood measuring method intended to objectively quantify this lexical phenomenon through the application of Williams’ (2001) lexical network model, which incorporates contextual information to compute the level of specialisation of sub-technical terms.

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2016-05-19
2024-04-18
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References

  1. Ahmad, Khurshid , Andrea Davies , Heather Fulford , and Monika Rogers
    1994 “What is a Term? The Semi-automatic Extraction of Terms from Text.” InTranslation Studies: An Interdiscipline, ed. by Snell-Hornby, M.F. Pöchhacker , and K. Kaindl , 267–278. Amsterdam: John Benjamins. doi: 10.1075/btl.2.33ahm
    https://doi.org/10.1075/btl.2.33ahm [Google Scholar]
  2. Alcaraz Varó, Enrique
    1994El Inglés Jurídico: Textos y Documentos. Madrid: Derecho.
    [Google Scholar]
  3. 2000El Inglés Profesional y Académico. Madrid: Alianza Editorial.
    [Google Scholar]
  4. Ananiadou, Sofia
    1988A Methodology for Automatic Term Recognition. PhD Thesis, University of Manchester, Institute of Science and Technology, United Kingdom.
  5. Aronson, Alan , and Françoise-Michel Lang
    2010 “An Overview of MetaMap: Historical Perspective and Recent Advances.” Journal of American Medical Informatics Association17 (3): 229–236. doi: 10.1136/jamia.2009.002733
    https://doi.org/10.1136/jamia.2009.002733 [Google Scholar]
  6. Baker, Mona
    1988 “Sub-technical Vocabulary and the ESP Teacher: An Analysis of some Rhetorical Items in Medical Journal Articles.” Reading in a Foreign Language4 (2): 91–105.
    [Google Scholar]
  7. Barrón-Cedeño, Alberto , Gerardo Sierra , Patrick Drouin , and Sofia Ananiadou
    2009 “An Improved Automatic Term Recognition Method for Spanish.” InProceedings of the 10th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2009), ed. by A. Gelbuck , 125–136. Berlin: Springer-Verlag. (users.dsic.upv.es/~lbarron/publications/2009/BarronTermsCICLING.pdf). AccessedJanuary 2016. doi: 10.1007/978‑3‑642‑00382‑0_10
    https://doi.org/10.1007/978-3-642-00382-0_10 [Google Scholar]
  8. Bourigault, Didier
    1992 “Surface Grammatical Analysis for the Extraction of Terminological Noun Phrases.” In Proceedings of the 5th International Conference on Computational Linguistics , 977–981. Nantes, France.
    [Google Scholar]
  9. Borja Albí, Anabel
    2000El Texto Jurídico en Inglés y su Traducción. Barcelona: Ariel.
    [Google Scholar]
  10. Cabré, María Teresa , Rosa Estopà , and Jorge Vivaldi
    2001 “Automatic Term Detection: A Review of Current Systems.” InRecent Advances in Computational Terminology, ed. by D. Bourigault , C. Jacquemin , and M.C. L’Homme , 53–87. Amsterdam: John Benjamins. doi: 10.1075/nlp.2.04cab
    https://doi.org/10.1075/nlp.2.04cab [Google Scholar]
  11. Chung, Teresa M
    2003 “A Corpus Comparison Approach for Terminology Extraction.” Terminology9 (2): 221–246. doi: 10.1075/term.9.2.05chu
    https://doi.org/10.1075/term.9.2.05chu [Google Scholar]
  12. Chung, Teresa M. , and Paul Nation
    2003 “Technical Vocabulary in Specialised Texts.” Reading in a Foreign Language15 (2): 103–116.
    [Google Scholar]
  13. Church, Kenneth W. , and Patrick Hanks
    1990 “Word Association Norms, Mutual Information, and Lexicography.” Computational Linguistics16 (1): 22–29.
    [Google Scholar]
  14. Church, Kenneth W. , and William Gale
    1995 “Inverse Document Frequency IDF: A Measure of Deviations from Poisson.” InProceedings of the Third Workshop on Very Large Corpora, ed. by D. Yarowsky and K. Church , 121–130. Cambridge: Massachusetts Institute of Technology Press.
    [Google Scholar]
  15. Cowan, Ronayne
    1974 “Lexical and Syntactic Research for the Design of EFL.” TESOL Quarterly8: 389–399. doi: 10.2307/3585470
    https://doi.org/10.2307/3585470 [Google Scholar]
  16. Coxhead, Averyl
    2000 “A New Academic Word List.” TESOL Quarterly34 (2): 213–238. doi: 10.2307/3587951
    https://doi.org/10.2307/3587951 [Google Scholar]
  17. Dagan, Ido , and Kenneth Church
    1994 “TERMIGHT: Identifying and Translating Technical Terminology.” In Proceedings of the 4th Conference on Applied Natural Language Processing , 34–40. Stuttgart, Germany (www.aclweb.org/anthology-new/A/A94/A94-1006.pdf). AccessedJanuary, 2016.
    [Google Scholar]
  18. Daille, Beatrice
    1996 “Study and Implementation of Combined Techniques for Automatic Extraction of Terminology.” InThe Balancing Act: Combining Symbolic and Statistical Approaches to Language, ed. by J.L. Klavans and P. Resnik , 29–36. Cambridge: Massachusetts Institute of Technology Press.
    [Google Scholar]
  19. David, Sophie , and Pierre Plante
    1990Termino1.0. Research Report of Centre d’Analyse de Textes par Ordinateur. Université du Québec, Montréal.
    [Google Scholar]
  20. Drouin, Patrick
    2003 “Term Extraction Using Non-technical Corpora as a Point of Leverage.” Terminology9 (1): 99–117. doi: 10.1075/term.9.1.06dro
    https://doi.org/10.1075/term.9.1.06dro [Google Scholar]
  21. Dunning, Ted
    1993 “Accurate Methods for the Statistics of Surprise and Coincidence”. Computational Linguistics19 (1): 61–74.
    [Google Scholar]
  22. Fahmi, Ismail , Gosse Bouma , and Lonneke van der Plas
    2007 “Improving Statistical Method Using Known Terms for Automatic Term Extraction.” InProceedings of Computational Linguistics in the Netherlands (CLIN 17), ed. by F. van Eynde , P. Dirix , I. Schuurman , and V. Vandeghinste , 1–8. Belgium: University of Leuven.
    [Google Scholar]
  23. Farrell, Paul
    1990Vocabulary in ESL: A Lexical Analysis of the English of Electronics and a Study of Semi-technical Vocabulary. Dublin: Centre for Language and Communication Studies.
    [Google Scholar]
  24. Flowerdew, John
    2001 “Concordancing as Tool in Course Design.” InSmall corpus Studies and ELT: Theory and Practice, ed. by M. Ghadessy , A. Henry , and R. Roseberry , 71–92. Amsterdam: John Benjamins. doi: 10.1075/scl.5.09flo
    https://doi.org/10.1075/scl.5.09flo [Google Scholar]
  25. Frantzi, Katerina T. , and Sophia Ananiadou
    1999 “The C/NC Value Domain Independent Method for Multi-word Term Extraction.” Journal of Natural Language Processing3 (2): 115–127.
    [Google Scholar]
  26. Frantzi, Katerina , Sofia Ananiadoua , and Hideki Mima
    2000 “Automatic Recognition of Multi-Word Terms: The C-value/NC-value Method.” International Journal on Digital Libraries3 (2): 115–130. doi: 10.1007/s007999900023
    https://doi.org/10.1007/s007999900023 [Google Scholar]
  27. Geffet, Maayan , and Ido Dagan
    2005 “The Distributional Inclusion Hypotheses and Lexical Entailment.” In Proceedings of the Annual Meeting of the ACL , 107–114. Michigan, USA.
    [Google Scholar]
  28. Heatley, Alex , and Paul Nation
    2002Range. Computer software. Wellington, New Zealand: Victoria University of Wellington.
    [Google Scholar]
  29. Jacquemin, Christian
    2001Spotting and Discovering Terms through NLP. Cambridge: Massachusetts Institute of Technology Press.
    [Google Scholar]
  30. Joslyn, Cliff , Patrick Paulson , and Karin Verspoor
    2008 “Exploiting Term Relations for Semantic Hierarchy Construction.” In Proceedings of the International Conference of Semantic Computing IEEE , 42–49. Santa Clara (CA), USA.
    [Google Scholar]
  31. Justeson, John S. , and Slava M. Katz
    1995 “Technical Terminology: Some Linguistic Properties and an Algorithm for Identification in Text.” Natural Language Engineering1 (1): 9–27. doi: 10.1017/S1351324900000048
    https://doi.org/10.1017/S1351324900000048 [Google Scholar]
  32. Kit, Chunyu , and Xiaoyue Liu
    2008 “Measuring Mono-word Termhood by Rank Difference via Corpus Comparison.” Terminology14 (2): 204–229. doi: 10.1075/term.14.2.05kit
    https://doi.org/10.1075/term.14.2.05kit [Google Scholar]
  33. Lemay, Chantal , Marie-Claude L’Homme , and Patrick Drouin
    2005 “Two Methods for Extracting “Specific” Single-Word Terms form Specialised Corpora.”International Journal of Corpus Linguistics10 (2): 227–255. doi: 10.1075/ijcl.10.2.05lem
    https://doi.org/10.1075/ijcl.10.2.05lem [Google Scholar]
  34. Loginova, Elizabeta , Anita Gojun , Helena Blancafort , María Guegan , Tatiana Gornostay , and Ulrich Heid
    . “Reference Lists for the Evaluation of Term Extraction Tools.” In Proceedings of TKE 2012: Terminology and Knowledge Engineering , 177–192. Madrid: Universidad Politécnica de Madrid. (www.ttc-project.eu/images/stories/TTC_TKE_2012.pdf), AccessedJanuary 2016.
    [Google Scholar]
  35. Marín, María José
    2014 “Evaluation of Five Single-word Term Recognition Methods on a Legal Corpus.” Corpora9 (1): 83–107. doi: 10.3366/cor.2014.0052
    https://doi.org/10.3366/cor.2014.0052 [Google Scholar]
  36. Marín, María José , and Camino Rea
    2012 “Structure and Design of the BLRC: A Legal Corpus of Judicial Decisions from the UK.” Journal of English Studies10: 131–145.
    [Google Scholar]
  37. Maynard, Diana , and Sofia Ananiadou
    2000 “TRUCKS: A Model for Automatic Multi-word Term Recognition”. Journal of Natural Language Processing8 (1): 101–125. doi: 10.5715/jnlp.8.101
    https://doi.org/10.5715/jnlp.8.101 [Google Scholar]
  38. Mellinkoff, David
    1963The Language of the Law. Boston: Little, Brown & Co.
    [Google Scholar]
  39. Nakagawa, Hiroshi , and Tatsunori Mori
    2002 “A Simple but Powerful Automatic Term Extraction Method.” In COLING-02 on COMPUTERM . Proceedings of the Second International Workshop on Computational Terminology , 1–7. Taipei, Taiwan.
    [Google Scholar]
  40. Nazar, Rogelio , and María Teresa Cabré
    2012 “Supervised Learning Algorithms Applied to Terminology Extraction.” InProceedings of the 10th Terminology and Knowledge Engineering ConferenceTKE 2012, ed. by G. Aguado de Cea , M.C. Suárez-Figueroa , R. García-Castro , and E. Montiel-Ponsoda , 209–217. Madrid: Ontology Engineering Group, Association for Terminology and Knowledge Transfer.
    [Google Scholar]
  41. Orts, María Ángeles
    2006Aproximación al Discurso Jurídico en Inglés: Las Pólizas de Seguro Marítimo de Lloyd’s. Madrid: Edisofer.
    [Google Scholar]
  42. Panzienza, Maria Teresa , Marco Pennacchiotti , and Fabio Massimo Zanzotto
    2005 “Terminology Extraction: An Analysis of Linguistic and Statistical Approaches.” Studies in Fuzziness and Soft Computing185: 225–279.
    [Google Scholar]
  43. Park, Younja , Roy Byrd , and Branimir Boguraev
    2002 “Automatic Glossary Extraction: Beyond Terminology Association.” In Proceedings of COLING’02 19th International Conference on Computational Linguistics , ed. by S.C. Zeng , 1–7. Taipei, Taiwan. doi: 10.3115/1072228.1072351
    https://doi.org/10.3115/1072228.1072351 [Google Scholar]
  44. Sclano, Francesco , and Paola Velardi
    2007 “A Web Application to Learn the Common Terminology of Interest Groups and Research Communities.” InProceedings of the Conference TIA-2007, ed. by C. Engehard and R.D. Kuntz , 85–94. Grenoble: Presses Universitaires de Grenoble.
    [Google Scholar]
  45. Scott, Mike
    2008WordSmith Tools Version 5. Liverpool: Lexical Analysis Software.
    [Google Scholar]
  46. Sparck-Jones, Kathleen
    1972 “A Statistical Interpretation of Term Specificity and its Application in Retrieval.” Journal of Documentation28: 11–21. doi: 10.1108/eb026526
    https://doi.org/10.1108/eb026526 [Google Scholar]
  47. Tiersma, Peter
    1999Legal Language. Chicago: The University of Chicago Press.
    [Google Scholar]
  48. Trimble, Louis
    1985English for Science & Technology: A Discourse Approach. Cambridge: Cambrige University Press.
    [Google Scholar]
  49. Vivaldi, Jorge
    2001Extracción de Candidatos a Término mediante Combinación de Estrategias Heterogéneas . PhD Thesis. Universidad Politécnica de Cataluña.
  50. Vivaldi, Jorge , Diego Cabrera , Luis Adrián , Gerardo Sierra and María Pozzi
    2012 “Using Wikipedia to Validate the Terminology Found in a Corpus of Basic Textbooks.” In Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC’12) , 3820–3827. Instambul: Instambul Lütfi Kırdar Convention and Exhibition Centre. (www.lrec-conf.org/proceedings/lrec2012/index.html). AccessedJanuary 2016.
    [Google Scholar]
  51. Wang, Karen , and Paul Nation
    2004 “Word Meaning in Academic English: Homography in the Academic Word List.” Applied Linguistics25 (3): 291–314. doi: 10.1093/applin/25.3.291
    https://doi.org/10.1093/applin/25.3.291 [Google Scholar]
  52. Weeds, Julie , David Weir , and Diana McCarthy
    2004 “Characterising Measures of Lexical Distributional Similarity.” In Proceedings of Coling-04 . 1–7, Geneva, Switzerland.
    [Google Scholar]
  53. West, Michael
    1953A General Service List of English Words. London: Longman.
    [Google Scholar]
  54. Williams, Geoffrey
    2001 “Mediating between Lexis and Texts: Collocational Networks in Specialised Corpora.” ASp, la Revue du GERAS31-33: 63–76. doi: 10.4000/asp.1782
    https://doi.org/10.4000/asp.1782 [Google Scholar]
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  • Article Type: Research Article
Keyword(s): corpus linguistics; ESP; Legal English; lexical networks; sub-technical terms
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