Knowledge Representation for Semantic Entailment and Question-Answering
Semantic entailment is the problem of determining if the meaning of a given sentence entails that of another.Question-answering can be reduced to this problem by rephrasing the question as a statement that is entailed by correct answers. In [Brazet al., ] we present a principled approach to semantic entailment that builds on inducing re-representations of text snippets into a hierarchical knowledge representation along with an optimization-based inferential mechanism that makes use of it to prove semantic entailment. This paper provides details and analysis of the knowledge representation and knowledge resources issues in the above approach. We analyze our system’s behavior on a collection of question-answer pairs and use it to motivate and explain some of the design decisions in our hierarchical knowledge representation, that is centered around a predicateargument type abstract representation of text.