Extractive summarisation of legal texts

Hachey, Ben; Grover, Claire

doi:10.1007/s10506-007-9039-z

Cited by 105 publications

(59 citation statements)

References 27 publications

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“…a categorisation of cue phrases used in science and regular expressions for matching them (Teufel et al 1999), or specially developed Named Entity Tools to identify judges, appellants, respondents, etc. (Hachey and Grover 2006), and report acceptable results for most of the categories, with some categories performing better than others. We do not rely on such manually developed resources, and restrict ourselves to linguistic features derived from the sentences themselves.…”

Section: Argument Extractionmentioning

confidence: 92%

“…This approach was initially used for scientific reports (Teufel et al 1999(Teufel et al , 2009). Hachey and Grover (2006) used argumentation zoning to create summaries for common law reports. Note that argumentative zoning, both for science (Teufel et al 1999) and for law (Hachey and Grover 2006), is very much aimed at capturing the argumentation used by the author of that paper or judgement.…”

Section: Argument Extractionmentioning

confidence: 99%

“…Hachey and Grover (2006) used argumentation zoning to create summaries for common law reports. Note that argumentative zoning, both for science (Teufel et al 1999) and for law (Hachey and Grover 2006), is very much aimed at capturing the argumentation used by the author of that paper or judgement. All sentences summarising previous papers or judgements are annotated as a single category (OTHER (Teufel et al 1999) or PROCEEDINGS (Hachey and Grover 2006).…”

Section: Argument Extractionmentioning

confidence: 99%

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Recognizing cited facts and principles in legal judgements

2017

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In common law jurisdictions, legal professionals cite facts and legal principles from precedent cases to support their arguments before the court for their intended outcome in a current case. This practice stems from the doctrine of stare decisis, where cases that have similar facts should receive similar decisions with respect to the principles. It is essential for legal professionals to identify such facts and principles in precedent cases, though this is a highly time intensive task. In this paper, we present studies that demonstrate that human annotators can achieve reasonable agreement on which sentences in legal judgements contain cited facts and principles (respectively, j ¼ 0:65 and j ¼ 0:95 for inter-and intra-annotator agreement). We further demonstrate that it is feasible to automatically annotate sentences containing such legal facts and principles in a supervised machine learning framework based on linguistic features, reporting per category precision and recall figures of between 0.79 and 0.89 for classifying sentences in legal judgements as cited facts, principles or neither using a Bayesian classifier, with an overall j of 0.72 with the human-annotated gold standard.

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Section: Argument Extractionmentioning

confidence: 92%

Section: Argument Extractionmentioning

confidence: 99%

Section: Argument Extractionmentioning

confidence: 99%

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Recognizing cited facts and principles in legal judgements

2017

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“…This method was originally defined for the summarization of scientific articles by Teufel and Moens (2002), but later studies such as Hachey and Grover (2006) applied the rhetorical status approach to the legal text domain for the context of English law.…”

Section: Rhetorical Structurementioning

confidence: 99%

“…We will now introduce the following four annotation tasks: 1. Issue Topic Identification -Issue Topic spans are marked in text, and iden- Earlier studies (Hachey and Grover, 2006;Saravanan and Ravindran, 2010) chose the sentence as the annotation unit and defined exclusive labeling, i.e., only one category can be assigned to each annotation unit. We also use exclusive labeling, but our definition of the smallest annotation unit is a comma-separated text unit.…”

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confidence: 99%

Annotation of argument structure in Japanese legal documents

Yamada¹,

Teufel²,

Tokunaga³

2017

Proceedings of the 4th Workshop on Argument Mining

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We propose a method for the annotation of Japanese civil judgment documents, with the purpose of creating flexible summaries of these. The first step, described in the current paper, concerns content selection, i.e., the question of which material should be extracted initially for the summary. In particular, we utilize the hierarchical argument structure of the judgment documents. Our main contributions are a) the design of an annotation scheme that stresses the connection between legal issues (called issue topics) and argument structure, b) an adaptation of rhetorical status to suit the Japanese legal system and c) the definition of a linked argument structure based on legal sub-arguments. In this paper, we report agreement between two annotators on several aspects of the overall task.

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Sentence simplification, compression, and disaggregation for summarization of sophisticated documents

Finegan-Dollak

Radev

2015

Asso for Info Science & Tech

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Sophisticated documents like legal cases and biomedical articles can contain unusually long sentences. Extractive summarizers can select such sentences—potentially adding hundreds of unnecessary words to the summary—or exclude them and lose important content. Sentence simplification or compression seems on the surface to be a promising solution. However, compression removes words before the selection algorithm can use them, and simplification generates sentences that may be ambiguous in an extractive summary. We therefore compare the performance of an extractive summarizer selecting from the sentences of the original document with that of the summarizer selecting from sentences shortened in three ways: simplification, compression, and disaggregation, which splits one sentence into several according to rules designed to keep all meaning. We find that on legal cases and biomedical articles, these shortening methods generate ungrammatical output. Human evaluators performed an extrinsic evaluation consisting of comprehension questions about the summaries. Evaluators given compressed, simplified, or disaggregated versions of the summaries answered fewer questions correctly than did those given summaries with unaltered sentences. Error analysis suggests 2 causes: Altered sentences sometimes interact with the sentence selection algorithm, and alterations to sentences sometimes obscure information in the summary. We discuss future work to alleviate these problems.

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Extractive summarisation of legal texts

Cited by 105 publications

References 27 publications

Recognizing cited facts and principles in legal judgements

Recognizing cited facts and principles in legal judgements

Annotation of argument structure in Japanese legal documents

Sentence simplification, compression, and disaggregation for summarization of sophisticated documents

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