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A System for Classification of Propositions of the Indian Supreme Court Judgements

Published: 04 December 2013 Publication History

Abstract

In this work, we describe a system for classification of propositions from legal judgements of the Supreme Court of India. The system was submitted for participation to the Information Access in the Legal Domain track at the Forum for Information Retrieval Evaluation (FIRE) 2013. The system uses a multi-class Maximum Entropy classifier and various specially designed features to capture the underlying characteristics of the legal propositions. The best performing feature set was chosen by 10-fold cross-validation over the training set. The system achieved an accuracy of 65.03% on the training set and an accuracy of 51.02% on the test set.

References

[1]
A. L. Berger, V. J. D. Pietra, and S. A. D. Pietra. A maximum entropy approach to natural language processing. Computational linguistics, 22(1):39--71, 1996.
[2]
P. R. Cohen and A. E. Howe. How evaluation guides ai research: The message still counts more than the medium. AI Magazine, 9(4):35, 1988.
[3]
B. Hachey and C. Grover. Sentence classification experiments for legal text summarisation. In Proceedings of the 17th Annual Conference on Legal Knowledge and Information Systems (Jurix), 2004.
[4]
C. D. Manning, M. Surdeanu, J. Bauer, J. Finkel, S. J. Bethard, and D. McClosky. The Stanford CoreNLP natural language processing toolkit. In Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 55--60, 2014.
[5]
Wikipedia. Supreme Court of India, 2014. {Online; Accessed 25-June-2014}.

Cited By

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  • (2018)Mining Supervisor Evaluation and Peer Feedback in Performance AppraisalsComputational Linguistics and Intelligent Text Processing10.1007/978-3-319-77116-8_47(628-641)Online publication date: 10-Oct-2018

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  1. A System for Classification of Propositions of the Indian Supreme Court Judgements

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    cover image ACM Other conferences
    FIRE '12 & '13: Proceedings of the 4th and 5th Annual Meetings of the Forum for Information Retrieval Evaluation
    December 2013
    105 pages
    ISBN:9781450328302
    DOI:10.1145/2701336
    • Editors:
    • Prasenjit Majumder,
    • Mandar Mitra,
    • Madhulika Agrawal,
    • Parth Mehta
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 04 December 2013

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    Author Tags

    1. legal proposition classification
    2. legal text classification
    3. text classification

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    FIRE '13
    FIRE '13: Forum for Information Retrieval Evaluation
    December 4 - 6, 2013
    New Delhi, India

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    Overall Acceptance Rate 19 of 64 submissions, 30%

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    • (2018)Mining Supervisor Evaluation and Peer Feedback in Performance AppraisalsComputational Linguistics and Intelligent Text Processing10.1007/978-3-319-77116-8_47(628-641)Online publication date: 10-Oct-2018

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