Relation Validation via Textual Entailment

This paper addresses a subtask of relation extraction, namely Relation Validation. Relation validation can be described as follows: given an instance of a relation and a relevant text fragment, the system is asked to decide whether this instance is true or not. Instead of following the common approaches of using statistical or context features directly, we propose a method based on textual entailment (called ReVaS). We set up two different experiments to test our system: one is based on an annotated data set; the other is based on real web data via the integration of ReVaS with an existing IE system. For the latter case, we examine in detail the two aspects of the validation process, i.e. directionality and strictness. The results suggest that textual entailment is a feasible way for the relation validation task.