Textual Entailment based on Semantic Similarity Using WordNet

We propose a method for automatic recognition of textual entailment based on word sense disambiguation using cosine similarity proposed by Abdalgader and Skabar. This algorithm finds semantic similarity of the sentence pairs- entailing text and entailed text. Both the hypothesis and text are converted into vectors using Jiang and Conrath similarity measure and cosine similarity is computed. Based on the cosine similarity score, a threshold is applied and the sentence pairs are classified into entailment and no entailment. The accuracy of the proposed scheme is better or comparable to many of the state of the art schemes.

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