Recognizing Textual Entailment with a Semantic Edit Distance Metric

  • Authors:
  • Miguel Rios;Alexander Gelbukh

  • Affiliations:
  • -;-

  • Venue:
  • MICAI '12 Proceedings of the 2012 11th Mexican International Conference on Artificial Intelligence
  • Year:
  • 2012

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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.