A graph-based relation extraction method for question answering system

Question Answering (QA) is the method of automatically answering a question asked by human in natural language using either a pre-structured database or a collection of documents. It is a rising new information service following the popularization of search engines. In this paper we introduce a graph-based QA system for reading comprehension tests that pick out the sentence in the passage that best answers a given question by extracting the relations. In order to improve the accuracy of the system, we do a gender analysis, morphological analysis and synonyms check along with coreference resolution. We tested our system with 60 comprehension passages each having five questions thereby a total of 300 questions and attained an accuracy of 79.67%. We achieved best results in terms of accuracy compared to the existing system having only 40%.