This paper proposes a knowledge representation model and a logic proving setting with axioms on demand successfully used for recognizing textual entailments. It also details a lexical inference system which boosts the performance of the deep semantic oriented approach on the RTE data. The linear combination of two slightly different logical systems with the third lexical inference system achieves 73.75% accuracy on the RTE 2006 data.
REF proposed for RTE a new knowledge representation model and a logic proving setting with axioms on demand.
A Logic-Based Semantic Approach To Recognizing Textual Entailment
International Conference On Computational Linguistics And Annual Meeting Of The Association For Computational Linguistics - Poster Sessions
Computer Science