Skip to main content
SpringerLink
Log in
Book cover

JSAI International Symposium on Artificial Intelligence

JSAI-isAI 2016: New Frontiers in Artificial Intelligence pp 284–298Cite as

Legal Yes/No Question Answering System Using Case-Role Analysis

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10247))

Abstract

A central issue of yes/no question answering is the usage of knowledge source given a question. While yes/no question answering has been studied for a long time, legal yes/no question answering largely differs from other domains. The most distinguishing characteristic is that legal issues require precise analysis of roles and relationships of agents named in sentences. We have developed a yes/no question answering system for answering questions about a statute legal domain. Our system uses case-role analysis, in order to find correspondences of roles and relationships between given problem sentences and knowledge source sentences. We applied our system to the JURISIN’s COLIEE (Competition on Legal Information Extraction/Entailment) 2016 task. Our system performance was better than systems of previous task participants and shared first place in current year’s task in Phase Two. This result shows the importance of the points described above, while revealing opportunities to continue further work on improving our system’s accuracy.

This is a preview of subscription content, log in via an institution.

References

  1. Lin, D., Pantel, P.: Discovery of inference rules for question-answering. Nat. Lang. Eng. 7(4), 343–360 (2001)

    Article  Google Scholar 

  2. Ravichandran, D., Hovy, E.: Learning surface text patterns for a question answering system. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 41–47 (2002)

    Google Scholar 

  3. Yu, H., Hatzivassiloglou, V.: Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. In: Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, pp. 129–136 (2003)

    Google Scholar 

  4. Pinto, D., McCallum, A., Wei, X., Croft, W.B.: Table extraction using conditional random fields. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval, pp. 235–242 (2003)

    Google Scholar 

  5. Cui, H., Sun, R., Li, K., Kan, M.-Y., Chua, T.-S.: Question answering passage retrieval using dependency relations. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 400–407 (2005)

    Google Scholar 

  6. Xue, X., Jeon, J., Croft, W.B.: Retrieval models for question and answer archives. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 475–482 (2008)

    Google Scholar 

  7. Bian, J., Liu, Y., Agichtein, E., Zha, H.: Finding the right facts in the crowd: factoid question answering over social media. In: Proceedings of the 17th International Conference on World Wide Web, pp. 467–476 (2008)

    Google Scholar 

  8. Voorhees, E.M., Harman, D.K.: TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing). The MIT Press, Cambridge (2005)

    Google Scholar 

  9. Kando, N., Kuriyama, K., Nozue, T.: NACSIS test collection workshop (NTCIR-1) (poster abstract). In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 299–300 (1999)

    Google Scholar 

  10. Braschler, M.: CLEF 2000—overview of results. In: Peters, C. (ed.) CLEF 2000. LNCS, vol. 2069, pp. 89–101. Springer, Heidelberg (2001). doi:10.1007/3-540-44645-1_9

    Chapter  Google Scholar 

  11. Kwok, C.C.T., Etzioni, O., Weld, D.S.: Scaling question answering to the web. In: Proceedings of the 10th International Conference on World Wide Web, pp. 150–161 (2001)

    Google Scholar 

  12. Etzioni, O., Cafarella, M., Downey, D., Kok, S., Popescu, A.-M., Shaked, T., Soderland, S., Weld, D.S., Yates, A.: Web-scale information extraction in knowitall: (preliminary results). In: Proceedings of the 13th International Conference on World Wide Web, pp. 100–110 (2004)

    Google Scholar 

  13. Jeon, J., Croft, W.B., Lee, J.H.: Finding similar questions in large question and answer archives. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 84–90 (2005)

    Google Scholar 

  14. Kanayama, H., Miyao, Y., Prager, J.: Answering yes/no questions via question inversion. In: The 24th International Conference on Computational Linguistics (COLING 2012), pp. 1377–1391 (2012)

    Google Scholar 

  15. Dumais, S., Banko, M., Brill, E., Lin, J., Ng, A.: Web question answering: is more always better? In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 291–298 (2002)

    Google Scholar 

  16. Ferrucci, D.: Introduction to ‘This is Watson’. IBM J. Res. Dev. 56(3.4), 1:1–1:15 (2012)

    Google Scholar 

  17. Ferrucci, D.A.: IBM’s Watson/DeepQA. SIGARCH Comput. Arch. News 39(3) (2011)

    Google Scholar 

  18. Arai, N.H.: The impact of AI—can a robot get into the university of Tokyo? Natl. Sci. Rev. 2(2), 135–136 (2015)

    Article  Google Scholar 

  19. The Todai Robot project. http://21robot.org/

  20. Dagan, I., Glickman, O., Magnini, B.: The PASCAL recognising textual entailment challenge. In: Quiñonero-Candela, J., Dagan, I., Magnini, B., d’Alché-Buc, F. (eds.) MLCW 2005. LNCS, vol. 3944, pp. 177–190. Springer, Heidelberg (2006). doi:10.1007/11736790_9

    Chapter  Google Scholar 

  21. Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B.: The third PASCAL recognizing textual entailment challenge. In: Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 1–9 (2007)

    Google Scholar 

  22. Negri, M., Marchetti, A., Mehdad, Y., Bentivogli, L., Giampiccolo, D.: Semeval-2012 task 8: cross-lingual textual entailment for content synchronization. In: Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the Main Conference and the Shared Task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation, pp. 399–407 (2012)

    Google Scholar 

  23. Shima, H., Kanayama, H., Lee, C., Lin, C., Mitamura, T., Miyao, Y., Shi, S., Takeda, K.: Overview of NTCIR-9 RITE: recognizing inference in text. In: NTCIR-9 Workshop, pp. 291–301 (2011)

    Google Scholar 

  24. Watanabe, Y., Miyao, Y., Mizuno, J., Shibata, T., Kanayama, H., Lee, C.-W., Lin, C.-J., Shi, S., Mitamura, T., Kando, N., Shima, H., Takeda, K.: Overview of the recognizing inference in text (RITE-2) at NTCIR-10. In: The NTCIR-10 Workshop, pp. 385–404 (2013)

    Google Scholar 

  25. Matsuyoshi, S., Miyao, Y., Shibata, T., Lin, C.-J., Shih, C.-W., Watanabe, Y., Mitamura, T.: Overview of the NTCIR-11 recognizing inference in text and validation (RITE-VAL) task. In: The 11th NTCIR (NII Testbeds and Community for Information Access Research) Workshop, pp. 223–232 (2014)

    Google Scholar 

  26. Dagan, I., Glickman, O., Magnini, B.: The PASCAL recognising textual entailment challenge. In: Proceedings of the PASCAL Challenges Workshop on Recognising Textual Entailment (2005)

    Google Scholar 

  27. Competition on Legal Information Extraction/Entailment (COLIEE-14), Workshop on Juris-informatics (JURISIN) 2014 (2014). http://webdocs.cs.ualberta.ca/~miyoung2/jurisin_task/index.html

  28. Kim, M.-Y., Goebel, R., Ken, S.: COLIEE-2015: evaluation of legal question answering. In: Ninth International Workshop on Juris-informatics (JURISIN 2015) (2015)

    Google Scholar 

  29. JUMAN (a User-Extensible Morphological Analyzer for Japanese). http://nlp.ist.i.kyoto-u.ac.jp/EN/index.php?JUMAN

  30. Japanese Dependency and Case Structure Analyzer KNP. http://nlp.ist.i.kyoto-u.ac.jp/EN/index.php?KNP

  31. Kim, M.-Y., Goebel, R., Kano, Y., Ken, S.: COLIEE-2016: evaluation of the competition on legal information extraction/entailment. In: Tenth International Workshop on Juris-informatics (JURISIN 2016) (2016)

    Google Scholar 

  32. John, A.K., Di Caro, L., Boella, G., Bartolini, C.: Team-Normas’ participation at the Coliee2016 bar legal exam competition. In: Tenth International Workshop on Juris-Informatics (JURISIN 2016) (2016)

    Google Scholar 

  33. Carvalho, D.S., Tran, V.D., Van Tran, K., Lai, V.D., Nguyen, M.-L.: Lexical to discourse-level corpus modeling for legal question answering. In: Tenth International Workshop on Juris-Informatics (JURISIN 2016) (2016)

    Google Scholar 

  34. Do, P.K., Nguyen, H.-T., Tran, C.-X., Nguyen, M.-T., Nguyen, M.L.: Legal question answering using ranking SVM and deep convolutional neural network. In: Tenth International Workshop on Juris-Informatics (JURISIN 2016) (2016)

    Google Scholar 

  35. Kim, K., Heo, S., Jung, S., Hong, K., Rhim, Y.-Y.: An ensemble based legal information retrieval and entailment system. In: Tenth International Workshop on Juris-Informatics (JURISIN 2016) (2016)

    Google Scholar 

  36. Kim, M.-Y., Xu, Y., Lu, Y., Goebel, R.: Legal question answering using paraphrasing and entailment analysis. In: Tenth International Workshop on Juris-Informatics (JURISIN 2016) (2016)

    Google Scholar 

Download references

Acknowledgements

This work was partially supported by MEXT Kakenhi, National Institute of Informatics, and JST CREST.

Author information

Authors and Affiliations

  1. Faculty of Informatics, Shizuoka University, Hamamatsu, Japan

    Ryosuke Taniguchi & Yoshinobu Kano

Authors
  1. Ryosuke Taniguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yoshinobu Kano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yoshinobu Kano .

Editor information

Editors and Affiliations

  1. Graduate School of Business Sciences, University of Tsukuba, Tokyo, Japan

    Setsuya Kurahashi

  2. Fujitsu Laboratories Ltd., Kanagawa, Japan

    Yuiko Ohta

  3. Chiba University, Chiba, Japan

    Sachiyo Arai

  4. National Institute of Informatics, Tokyo, Japan

    Ken Satoh

  5. Ochanomizu University, Tokyo, Japan

    Daisuke Bekki

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Taniguchi, R., Kano, Y. (2017). Legal Yes/No Question Answering System Using Case-Role Analysis. In: Kurahashi, S., Ohta, Y., Arai, S., Satoh, K., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2016. Lecture Notes in Computer Science(), vol 10247. Springer, Cham. https://doi.org/10.1007/978-3-319-61572-1_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-61572-1_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61571-4

  • Online ISBN: 978-3-319-61572-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation