Question Answering over Structured Data: an Entailment-Based Approach to Question Analysis
Matteo Negri, Milen Kouylekov · 2009
This paper addresses question analysis in the framework of Question Answering over struc-tured data. The problem is set as a relation extraction task, where all the relations of inter-est in a given domain have to be extracted from natural language questions. The proposed ap-proach applies the notion of Textual Entailment to compare the input questions with a reposi-tory of relational textual patterns. The under-lying assumption is that a question expresses a certain relation if a pattern for that relation is entailed by the question. We report on a number of experiments, testing different simple distance-based entailment algorithms over a dataset of 1487 English questions covering the domain of cultural events in a town, and 75 relations that are relevant in this domain. The positive results obtained demonstrate the feasibility of the over-all approach, and its effectiveness in the proposed QA scenario.