Towards automatic generation of catchphrases for legal case reports

Authors:
Filippo Galgani;Paul Compton;Achim Hoffmann
Affiliations:
School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia;School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia;School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia
Venue:
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II
Year:
2012

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Abstract

This paper presents the challenges and possibilities of a novel summarisation task: automatic generation of catchphrases for legal documents. Catchphrases are meant to present the important legal points of a document with respect of identifying precedents. Automatically generating catchphrases for legal case reports could greatly assist in searching for legal precedents, as many legal texts do not have catchphrases attached. We developed a corpus of legal (human-generated) catchphrases (provided with the submission), which lets us compute statistics useful for automatic catchphrase extraction. We propose a set of methods to generate legal catchphrases and evaluate them on our corpus. The evaluation shows a recall comparable to humans while still showing a competitive level of precision, which is very encouraging. Finally, we introduce a novel evaluation method for catchphrases for legal texts based on the known Rouge measure for evaluating summaries of general texts.