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Textual Entailment for Cybersecurity: an Applicative Case

Livio Robaldo Orcid Logo, Giovanni Siragusa, Luigi Di Caro, Andrea Violato

Journal of Applied Logics, Volume: 8, Issue: 4, Pages: 975 - 992

Swansea University Author: Livio Robaldo Orcid Logo

Abstract

Recognizing Textual Entailment (RTE) is the task of recognizing the relation between two sentences, in order to measure whether and to what extent one of the two is inferred from the other. It is used in many Natural Language Processing (NLP) tasks. In the last decades, with the digitization of many...

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Published in: Journal of Applied Logics
ISSN: 2631-9810 2631-9829
Published: College Publications 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa56726
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Abstract: Recognizing Textual Entailment (RTE) is the task of recognizing the relation between two sentences, in order to measure whether and to what extent one of the two is inferred from the other. It is used in many Natural Language Processing (NLP) tasks. In the last decades, with the digitization of manylegal documents, NLP applied to the legal domain has became prominent, due to the need of knowing which norms are complied with in case other norms are. In this context, from a set of obligations that are known to be complied with, RTE may be used to infer which other norms are complied with as well. We propose a dataset, regarding cybersecurity controls, for RTE on the legal domain. The dataset has been constructed using information available online, provided by domain experts from NIST (https://www.nist.gov).
College: Hillary Rodham Clinton School of Law
Issue: 4
Start Page: 975
End Page: 992