Corpus-based collocation research targeted at Japanese language learners
Keywords:Japanese language, collocations, second-language acquisition, language learning, corpora and tools
AbstractThis paper discusses corpus-based research on collocations, introduces various tools for querying and extracting Japanese collocations and presents an analysis of Japanese collocations using language corpora and related tools. First, major corpus query tools such as Sketch Engine, NINJAL-NLP, Natsume, Chunagon, which can be used by learners and teachers of Japanese language, are briefly described. Focus then shifts to adjectival and nominal collocates and the resource "Collocation data of adjectives and nouns" which consists of adjective headwords and their nominal collocates extracted from two large corpora, BCCWJ and JpTenTen: 500 adjectives and 9,218 collocate nouns, and 500 adjectives and 23,220 collocate nouns from each corpus respectively. Finally, it is shown that corpus-based resources can be used in the creation of reference materials for learners of the Japanese language. The benefits of empirical research into collocations are also shown by comparing the obtained results with collocations in textbooks for Japanese as foreign language.
Himeno, M. (ed.) (2012) Kenkyusha Japanese Collocation Dictionary (Kenkyūsha Nihongo Korokēshon Jiten). Tokyo: Kenkyusha
Hodošček, B. and Nishina, K. (2012) Japanese Learning Support Systems: Hinoki Project Report. Acta Linguistica Asiatica 2(3). Ljubljana: Ljubljana University Press, 95-124.
Imai, S., Akasegawa, S., Pardeshi, P. (2013) Development of NLT: the Search Tool for Tsukuba Web Corpus, Proceeding of the 3rd Japanese corpus linguistics workshop, Department of Corpus Studies/Center for Corpus Development, NINJAL, 199-206.
Kawahara, D. and Kurohashi, S. (2006) Case Frame Compilation from the Web using High-Performance Computing. In: Proceedings of the 5th International Conference on Language Resources and Evaluation (LREC2006).
Kilgarriff, A., Rychly, P., Smrz, P. and Tugwell, D. (2004) The Sketch Engine. In: G. Williams and S. Vessier (eds) Proceedings of Euralex, 105–16. Bretagne, France: Université de Bretagne-Sud.
Maekawa, K., Yamazaki, M., Ogiso, T., Maruyama, T., Ogura, H., Kashino, W., Koiso, H., Yamaguchi, M., Tanaka, M. and Den, Y. (2013) Balanced corpus of contemporary written Japanese. Language Resources and Evaluation. Netherlands: Springer
McEnery, T. and Hardie, A. (2012) Corpus Linguistics: Method, Theory and Practice. Cambridge Textbooks in Linguistics. Cambridge University Press
Nation, P. (2001) Learning vocabulary in another language. Cambridge: Cambridge University Press
Nishina, K. (2011). Development and evaluation of the writting support system Natsume using, the balanced corpus (in Japanese). Tokutei ryōiki kenkyū »Nihongo kōpasu« Heisei 22 nendo kōkai wākushoppu yokōshū. Tokyo: Monbukagakushō kagakukenkyūhi tokuteiryōiki kenkyū 'Nihongo kōpasu' sōkatsu ban. 215-224.
Oso M and Takizawa, N. (2003) Corpus-based study on Japanese education: About collocations and their misuse (in Japanese). Japanese Language 22(5). Meiji shoin, 234-244.
Pardeshi, P. and Akasegawa, S. (2010). BCCWJ wo katsuyō shita kihon dōshi handobukku sakusei: kōpasu braujingu shisutemu NINJAL-LWP no tokuchō to kinō. Tokutei ryōiki kenkyū Nihongo kōpasu Gendai Nihongo kakikotoba kinkō kōpasu kansei kinen yokōshū. 205-216.
Srdanović, I. (2013a) Description of Adjective and Noun Collocations Based on Large-Scale Corpora: Towards Dictionary for Japanese Language Learners (in Japanese). Kokuritsu kokugo kenkyūjo ronshū (NINJAL Research Papers) 6.
Srdanović, I. (2013b) Japanese i-adjectives as short and long-word units: implications for language learning. In: Proceedings of the Conference of the Pacific Association for Computational Linguistics (PACLING), 8 pp (CD-rom).
Srdanović, I. and Sakoda, K. (2013) Analysis of learner’s production of adjectives using the Japanese language learner’s corpus C-JAS: the case of takai. Acta Linguistica Asiatica, 3(2), 9-24.
Srdanović, I., Erjavec T. and Kilgarriff, A. (2008) A web corpus and word-sketches for Japanese. Shizen gengo shori (Journal of Natural Language Processing) 15(2), 137-159.
Srdanović, I., Suchomel, V., Ogiso, T, Kilgarriff, A. (2013) Japanese Language Lexical and Grammatical Profiling Using the Web Corpus JpTenTen (in Japanese).In: Proceeding of the 3rd Japanese corpus linguistics workshop. Tokyo: NINJAL, Department of Corpus Studies/Center for Corpus Development, 229-238.
How to Cite
Copyright (c) 2014 Irena SRDANOVIĆ
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors are confirming that they are the authors of the submitting article, which will be published online in journal Acta Linguistica Asiatica by Ljubljana University Press, Faculty of Arts (University of Ljubljana, Faculty of Arts, Aškerčeva 2, 1000 Ljubljana, Slovenia). Author’s name will be evident in the article in journal. All decisions regarding layout and distribution of the work are in hands of the publisher.
- Authors guarantee that the work is their own original creation and does not infringe any statutory or common-law copyright or any proprietary right of any third party. In case of claims by third parties, authors commit their self to defend the interests of the publisher, and shall cover any potential costs.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.