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AILA 2021: Shared task on Artificial Intelligence for Legal Assistance

Published: 26 January 2022 Publication History

Abstract

AILA 2021 was the third edition of the Shared task on Artificial Intelligence for Legal Assistance, that was organized with the FIRE 2021 conference. This year two tasks were offered. While the rhetorical role labelling task was continued from last year, a new Legal Judgement Summarization task was introduced in the current edition. In the Rhetorical Role Labelling task, given a case document, the sentences in the document were to be classified into 7 rhetorical roles – Fact, Ruling by Lower Court, Argument, Precedent, Statute, Ratio of the decision and Ruling by Present Court. The legal judgement summarization task consisted of two subtasks. Subtask (a) was a binary classification task that required participants to identify ‘summary-worthy’ sentences in a court judgement. For subtask (b) participants had to automatically generate a summary from a given court judgement. Datasets for both tasks were created by annotating publicly available judgments from the Supreme court of India.

References

[1]
Paheli Bhattacharya, Kripabandhu Ghosh, Saptarshi Ghosh, Arindam Pal, Parth Mehta, Arnab Bhattacharya, and Prasenjit Majumder. 2019. Overview of the FIRE 2019 AILA track: Artificial Intelligence for Legal Assistance. In Proceedings of FIRE 2019 - Forum for Information Retrieval Evaluation (Kolkata, India).
[2]
Paheli Bhattacharya, Parth Mehta, Kripabandhu Ghosh, Saptarshi Ghosh, Arindam Pal, Arnab Bhattacharya, and Prasenjit Majumder. 2020. Overview of the FIRE 2020 AILA track: Artificial Intelligence for Legal Assistance. In Proceedings of FIRE 2020 - Forum for Information Retrieval Evaluation (Hyderabad, India).
[3]
Paheli Bhattacharya, Shounak Paul, Kripabandhu Ghosh, Saptarshi Ghosh, and Adam Wyner. 2019. Identification of Rhetorical Roles of Sentences in Indian Legal Judgments. In Proc. International Conference on Legal Knowledge and Information Systems (JURIX).
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Sourav Dutta. 2021. Categorizing Roles of Legal Texts via SequenceTagging on Domain-Specific Language Models. In FIRE 2021 (Working Notes) (India).
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Shaz Furniturewala, Racchit Jain, Vijay Kumari, and Yashvardhan Sharma. 2021. Legal Text Classification and Summarization using Transformers and Joint Text Features. In FIRE 2021 (Working Notes) (India).
[6]
Deepali Jain, Malaya Dutta Borah, and Anupam Biswas. 2021. Summarization of Indian Legal Judgement Documents via Ensembling of Contextual Embedding based MLP Models. In FIRE 2021 (Working Notes) (India).
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Guneet Singh Kohli, Prabsimran Kaur, and Jatin Bedi. 2021. Automatic Detection of Rhetorical Role Labels using ERNIE2.0 and RoBERTa. In FIRE 2021 (Working Notes) (India).
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Arpan Mandal, Kripabandhu Ghosh, Arnab Bhattacharya, Arindam Pal, and Saptarshi Ghosh. 2017. Overview of the FIRE 2017 IRLeD Track: Information Retrieval from Legal Documents. In Working notes of Annual Meeting of the Forum for Information Retrieval Evaluation (FIRE) – CEUR workshop proceedings, Volume 2036. 63–68.
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Vedant Parikh, Vidit Mathur, Parth Mehta, Namita Mittal, and Prasenjit Majumder. 2021. LawSum: A weakly supervised approach for Indian Legal Document Summarization. arXiv preprint arXiv:2110.01188v3(2021).

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FIRE '21: Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation
December 2021
113 pages
ISBN:9781450395960
DOI:10.1145/3503162
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 January 2022

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Author Tags

  1. Headnote generation
  2. Legal data analytics
  3. Legal document summarization
  4. Rhetorical role labelling
  5. Semantic segmentation

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  • Refereed limited

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FIRE 2021
FIRE 2021: Forum for Information Retrieval Evaluation
December 13 - 17, 2021
Virtual Event, India

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Overall Acceptance Rate 19 of 64 submissions, 30%

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