@inproceedings{mullick-etal-2022-evaluation,
title = "An Evaluation Framework for Legal Document Summarization",
author = "Mullick, Ankan and
Nandy, Abhilash and
Kapadnis, Manav and
Patnaik, Sohan and
R, Raghav and
Kar, Roshni",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.508/",
pages = "4747--4753",
abstract = "A law practitioner has to go through numerous lengthy legal case proceedings for their practices of various categories, such as land dispute, corruption, etc. Hence, it is important to summarize these documents, and ensure that summaries contain phrases with intent matching the category of the case. To the best of our knowledge, there is no evaluation metric that evaluates a summary based on its intent. We propose an automated intent-based summarization metric, which shows a better agreement with human evaluation as compared to other automated metrics like BLEU, ROUGE-L etc. in terms of human satisfaction. We also curate a dataset by annotating intent phrases in legal documents, and show a proof of concept as to how this system can be automated."
}
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<abstract>A law practitioner has to go through numerous lengthy legal case proceedings for their practices of various categories, such as land dispute, corruption, etc. Hence, it is important to summarize these documents, and ensure that summaries contain phrases with intent matching the category of the case. To the best of our knowledge, there is no evaluation metric that evaluates a summary based on its intent. We propose an automated intent-based summarization metric, which shows a better agreement with human evaluation as compared to other automated metrics like BLEU, ROUGE-L etc. in terms of human satisfaction. We also curate a dataset by annotating intent phrases in legal documents, and show a proof of concept as to how this system can be automated.</abstract>
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%0 Conference Proceedings
%T An Evaluation Framework for Legal Document Summarization
%A Mullick, Ankan
%A Nandy, Abhilash
%A Kapadnis, Manav
%A Patnaik, Sohan
%A R, Raghav
%A Kar, Roshni
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Thirteenth Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F mullick-etal-2022-evaluation
%X A law practitioner has to go through numerous lengthy legal case proceedings for their practices of various categories, such as land dispute, corruption, etc. Hence, it is important to summarize these documents, and ensure that summaries contain phrases with intent matching the category of the case. To the best of our knowledge, there is no evaluation metric that evaluates a summary based on its intent. We propose an automated intent-based summarization metric, which shows a better agreement with human evaluation as compared to other automated metrics like BLEU, ROUGE-L etc. in terms of human satisfaction. We also curate a dataset by annotating intent phrases in legal documents, and show a proof of concept as to how this system can be automated.
%U https://aclanthology.org/2022.lrec-1.508/
%P 4747-4753
Markdown (Informal)
[An Evaluation Framework for Legal Document Summarization](https://aclanthology.org/2022.lrec-1.508/) (Mullick et al., LREC 2022)
ACL
- Ankan Mullick, Abhilash Nandy, Manav Kapadnis, Sohan Patnaik, Raghav R, and Roshni Kar. 2022. An Evaluation Framework for Legal Document Summarization. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 4747–4753, Marseille, France. European Language Resources Association.