Cover not available

In:Recent Advances in Multiword Units in Machine Translation and Translation Technology
Edited by Johanna Monti, Gloria Corpas Pastor, Ruslan Mitkov and Carlos Manuel Hidalgo-Ternero
[Current Issues in Linguistic Theory 366] 2024
► pp. 218–242

Get fulltext from our e-platform
JBE logo with link
PDF logo with download linkDownload Book PDF
EPUB logo with download linkDownload Book EPUB
authorization required

Chapter 12
A comprehensive Japanese MWE lexicon

JMWEL

 | Kurume Institute of Technology, emeritus, Japan
 | Fukuoka University, Japan
 | CJKI Co., Japan
 | Fukuoka University, emeritus, Japan
Published online: 7 November 2024
DOI logo with link
https://doi.org/10.1075/cilt.366.12tak
Abstract
JMWEL (Japanese MWE Lexicon) is a comprehensive lexicon of Japanese Multiword Expressions (MWEs) with a rich set of grammatical attributes fine-tuned for phrase-based processing of a wide range of Japanese documents. It has about 160,000 MWE lemmas covering almost every kind of linguistically idiosyncratic but commonly used Japanese phrases, e.g., idioms, quasi-idioms, collocations, quasi-collocations, clichés, quasi-clichés, institutionalized phrases, proverbs, and old sayings, excepting technical terms in specialized fields or named entities. JMWEL consists of sixteen sub-lexicons reflecting their distinctive features. The comprehensiveness of the collected MWEs and the detailed morpho-syntactic information given to each MWE, which may include internal modifiers, are notable features of JMWEL. In this paper, we introduce the newest version of JMWEL.
Article outline
  • 1.Introduction
  • 2.MWE lemma
    • 2.1Non-compositionality
    • 2.2Probabilistically idiosyncratic MWEs
    • 2.3Distribution of MWEs in JMWEL
  • 3.Organization of JMWEL
    • 3.1Sub-lexicons compiled based on grammatical functions
    • 3.2Sub-lexicons organized by topic
  • 4.Data entries in JMWEL
    • 4.1Type label
    • 4.2Lemma
    • 4.3Constituent morphemes
    • 4.4Orthographic variants
    • 4.5Syntactic function
    • 4.6Morpho-syntactic structure
    • 4.7Internal modification
    • 4.8Forward context condition
    • 4.9Backward context condition
    • 4.10Inflection
    • 4.11Interpretation
  • 5.Applications
  • 6.Related work
  • 7.Concluding remarks
  • Acknowledgements
  • Notes
  • References
References (16)
References
Biber, D., Johansson, S., Leech, G., Conrad, S., & Finegan, E. (Eds.) (1999). Longman grammar of spoken and written English. Pearson Education.Google Scholar logo with link to Google Scholar
Church, K. (2011). How many multiword expressions do people know? Proceedings of the Workshop on Multiword Expressions: From Parsing and Generation to the Real World (MWE 2011), (pp. 137–144). Invited Talk.Google Scholar logo with link to Google Scholar
Constant, M., Eryigit, G., Monti, J., van der Plas, L., Ramisch, C., Rosner, M., & Todirascu, A. (2017). Multiword expression processing: A survey. Computational Linguistics, 43(4), 837–892. Google Scholar logo with link to Google Scholar
Corrigan, R., Moravcsik, E. A., Ouali, H., & Wheatley, K. (Eds.) (2009). Formulaic language, vol.1 distribution and historical change. John Benjamins. Google Scholar logo with link to Google Scholar
Cowie, A. P. (Ed.) (1998). Phraseology: Theory, analysis, and applications. (Oxford Studies in Lexicography and Lexicology). Clarendon Press. Google Scholar logo with link to Google Scholar
Fillmore, C., Kay, P., & O’Connor, M. C. (1988). Regularity and idiomatical grammatical construction: The case of let alone. Language, 64, 501–538. Google Scholar logo with link to Google Scholar
Hashimoto, C., & Kawahara, D. (2008). Construction of an idiom corpus and its application to idiom identification based on WSD incorporating idiom-specific features. Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing (pp. 992–1001).
Kudo, T., & Kazawa, H. (2009). Japanese web n-gram Version 1. Linguistic Data Consortium 2009. T08.
Ramisch, C. (2017). Putting the Horses Before the Cart: Identifying Multiword Expressions Before Translation. The EUROPHRAS 2017 (MUMTTT 2017). Proceedings (pp. 69–84). Invited Talk. Google Scholar logo with link to Google Scholar
Sag, I. A., Baldwin, T., Bond, F., Copestake, A., & Flickinger, D. (2002). Multiword expressions: A pain in the neck for NLP. Proceedings of the 3rd International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2002) (pp. 1–15).
Savary, A., Cordeiro, S. R., & Ramisch, C. (2019). Without lexicons, multiword expression identification will never fly: A position statement. Proceedings of EUROPHRAS 2019 (pp. 79–91).
Shudo, K. (2011). Research studio for Japanese language processing, [URL]
(1973). On machine translation from Japanese into English for a technical field. Journal of the Information Processing Society of Japan, 14(9), 661–668. (Japanese title: 専門分野を対象とした日英機械翻訳について).Google Scholar logo with link to Google Scholar
Shudo, K., Fujita, T., & Yoshida, S. (1978). On the processing of annexational expressions in Japanese. Proceedings of the international conference on the Computational Linguistics, COLING78 (pp. 53.1–53.11).
Tanabe, T, Takahashi, M., & Shudo, K. (2014). A lexicon of multiword expressions for linguistically precise, wide-coverage natural language processing. Computer Speech and Language, 28(6), 1317–1339. Elsevier. Google Scholar logo with link to Google Scholar
Zaninello, A., & Birch, A. (2020). Multiword expression aware neural machine translation. Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) (pp. 3816–3825).
Mobile Menu Logo with link to supplementary files background Layer 1 prag Twitter_Logo_Blue