Abstract. The question-answering system developed by this research matches one-sentence-long user questions to a number of question templates that cover the conceptual model of the database and describe the concepts, their attributes, and the relationships in form of natural language questions. A question template resembles a frequently asked question (FAQ). Unlike a static FAQ, however, a question template may contain entity slots that are replaced by data instances from the underlying database. During the question-answering process, the system retrieves relevant data instances and question templates, and offers one or several interpretations of the original question. The user selects an interpretation to be answered.

Automated Question-Answering aims at delivering concise information that contains answers to user questions. This paper reviews and compares three main question-answering approaches based on Natural Language Processing, Information Retrieval, and question templates, eliciting their differences and the context of application that best suits each of them.

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