Recognizing textual entailment with a semantic edit distance metric

Miguel Rios, Alexander Gelbukh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

We present a Recognizing Textual Entailment(RTE) system based on different similarity metrics. The metricsused are string-based metrics and the Semantic Edit DistanceMetric, which is proposed in this paper to address limitationsof known semantic-based metrics and to support the decisionsmade by a simple method based on lexical similarity metrics.We add the scores of the metrics as features for a machinelearning algorithm. The performance of our system is comparablewith the average performance of the Recognizing TextualEntailment Challenges, though lower than that of the state-ofthe-art methods.

Original languageEnglish
Title of host publicationProceedings of Special Session - Revised Papers, 11th Mexican International Conference on Artificial Intelligence 2012
Subtitle of host publicationAdvances in Artificial Intelligence and Applications, MICAI 2012
Pages15-20
Number of pages6
DOIs
StatePublished - 2012
Event11th Mexican International Conference on Artificial Intelligence 2012: Advances in Artificial Intelligence and Applications, MICAI 2012 - San Luis Potosi, Mexico
Duration: 27 Oct 20124 Nov 2012

Publication series

NameProceedings of Special Session - Revised Papers, 11th Mexican International Conference on Artificial Intelligence 2012: Advances in Artificial Intelligence and Applications, MICAI 2012

Conference

Conference11th Mexican International Conference on Artificial Intelligence 2012: Advances in Artificial Intelligence and Applications, MICAI 2012
Country/TerritoryMexico
CitySan Luis Potosi
Period27/10/124/11/12

Keywords

  • Natural Language Processing
  • Recognizing Textual

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