A study on textual entailment


In this paper we study a graph-based approach to the task of textual entailment between a Text and Hypothesis. The approach takes into account the full lexicosyntactic context of both the Text and Hypothesis and relies heavily on the concept of subsumption. It starts with mapping the Text and Hypothesis into graph structures where nodes represent concepts and edges represent lexico-syntactic relations among concepts. Based on a subsumption score between the Text-graph and Hypothesis-graph an entailment decision is then made. The impact of synonymy on entailment is quantified and discussed. An important advantage of our solution is the ability to customize it so that high-confidence results are obtained. © 2005 IEEE.

Publication Title

Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI