Abstract
In this paper we describe that the hierarchical tag context tree (HTCT) approach improves the accuracy of semantic role labeling on Japanese text. In Japanese language there are functional multiword expressions such as no-tame-ni and yotte that have potential to designate semantic relations between a predicate and its arguments. Since these expressions come to the end part of each argument, the performance of the CRF-based semantic role labeler can be improved by taking into account the last morphemes of each argument as features. We apply our proposed system to the annotated corpus of semantic role labels on a balanced Japanese corpus. The experimental results show that the CRF-based labeler with features extracted by HTCT approach outperforms the normal CRF-based labeler.
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Notes
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The EDR corpus [12] also contains SRLs on Japanese texts, however, the texts are not balanced, thus we select PT corpus.
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See more details of the annotated corpus at http://pth.cl.cs.okayama-u.ac.jp.
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We set the threshold to 0Â in these experiments.
References
Baker, C.F., Fillmore, C.J., Lowe, J.B.: The Berkeley FrameNet project. In: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics, pp. 86–90 (1998)
Palmer, M., Gildea, D., Kingsbury, P.: The proposition bank: an annotated corpus of semantic roles. Computat. Linguist. 31(1), 71–105 (2005)
Gildea, D., Jurafsky, D.: Automatic labeling of semantic roles. Comput. Linguist. 28(3), 1–45 (2002)
Surdeanu, M., Johansson, R., Meyers, A., Marquez, L., Nivre, J.: The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies. In: Proceedings of the 12th Conference on Computational Natural Language Learning, pp. 159–177 (2008)
Palmer, M., Gildea, D., Xue, N.: Semantic Role Labeling. Morgan & Claypool Publishers, San Rafael (2009)
Kawahara, D., Kurohashi, S., Hashida, K.: Construction of a Japanese relevance-tagged corpus. In: Proceedings of the 8th Annual Meeting of the Association for Natural Language Processing, pp. 495–498 (2007) (in Japanese)
Iida, R., Komachi, M., Inui, K., Matsumoto, Y.: Annotating a Japanese text corpus with a predicate-argument and coreference relations. In: Proceedings of the 1st Linguistic Annotation Workshop, pp. 132–139 (2007)
Komachi, M., Iida, R.: Annotating a Japanese balanced corpus (BCCWJ) with a predicate-argument and coreference relations. In: Workshop for Japanese Corpus, pp. 352–330 (2011) (in Japanese)
Ohara, K., Kato, J., Saito, H.: Annotation of Japanese framenet to BCCWJ. In: Proceedings of the Workshop of Japanese Corupus in Grant-in-Aid For Scientific Research on Priority Areas, pp. 513–518 (2011) (in Japanese)
Takeuchi, K., Ueno, M., Takeuchi, N.: Annotating semantic role information to Japanese balanced corpus. In: Proceedings of MAPLEX 2015 (2015)
Maekawa, K.: Balanced corpus of contemporary written Japanese. In: Proceedings of the 6th Workshop on Asian Language Resources (ALR), pp. 101–102 (2008)
EDR, EDR: Electric Dictionary the Second Edition, Japan Electronic Dictionary Research Institute, Ltd. (1995)
Haruno, M., Matsumoto, Y.: Mistake-driven mixture of hierarchical tag context trees. In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics, pp. 230–237 (1997)
Acknowledgments
This research received support from JSPS KAKENHI Grant Number 26370485.
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Ishihara, Y., Takeuchi, K. (2016). Japanese Semantic Role Labeling with Hierarchical Tag Context Trees. In: Hasida, K., Purwarianti, A. (eds) Computational Linguistics. PACLING 2015. Communications in Computer and Information Science, vol 593. Springer, Singapore. https://doi.org/10.1007/978-981-10-0515-2_2
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