Corpus-based Pattern Induction for a Knowledge-based Question Answering Approach

In this paper, we present an approach which, given a knowledge base and an appropriate text corpus, automatically induces patterns which can be used to query the knowledge base. We do not only consider simple questions but text problems consisting of several sentences. Answers to complex text problems are determined by an inference process which computes the answer on the basis of the background knowledge in the knowledge base (KB) as well as the textual description of the problem. The question formulated in natural language thus needs to be translated into appropriate KB structures and queries. Our approach to translating the natural language question uses an underlying corpus and the knowledge base to derive meaningful and relevant patterns which can then be used to process the questions and capture their meaning with respect to the underlying knowledge base. We apply our approach to advanced placement (AP) questions in three areas: physics, chemistry and biology. We report results of a first evaluation of the translation procedure for the three domains.