Question Answering (QA) Basics

The main objective of the question answering (QA) task is to provide relevant answers in response to questions asked in natural language through either a prestructured database or a collection of natural language documents [11]. The basic architecture usually consists of three components: a question processing unit, a document processing unit and an answer processing unit. The question processing unit first analyzes the structure of the given question and transforms the question into a meaningful format compatible with the QA domain. The document processing unit generates a dataset or a model that provides information for answer generation. The answer processing unit extracts the answer from information and formatted questions. In this chapter, we discuss the QA task from the following aspects: rule-based methods, information retrievalInformation retrieval-based methods, neural semantic parsingNeural semantic parsing-based methods and approaches taking knowledge base into account.