A Factoid Question Answering System Using Answer Pattern Matching

Abstract

In this paper, we describe a Turkish factoid QA system which uses surface level patterns called answer patterns in order to extract the answers from the documents that are retrieved from the web. The answer patterns are learned using five different answer pattern extraction methods with the help of the web. Our novel approach to extract named entity tagged answer patterns and our new confidence factor assignment approach have an important role in the successful performance of our QA system. We also describe a novel query expansion technique to improve the performance. The evaluation results show that the named entity tagging in answer patterns and the query expansion leads to significant performance improvement. The scores of our QA system are comparable with the results of the best factoid QA systems in the literature.