Question Answering is an NLP task that aims to provide an exact answer to a natural language question. Earlier research in this area focussed on short factoid questions that could often be answered just with word matching (e.g. What is the capital of Norway?), but more recent work, such as the Watson Jeopardy Challenge and the CLEF QA for Machine Reading task aims to answer questions that require inference and integration of background knowledge. These sort of questions require more sophisticated processing and a more abstract understanding of the meaning of both the question and potential answer sources.
This project will investigate the integration of semantic information acquired from a large unification-based parser with shallower forms of analysis for the purposes of question answering. This will require knowledge of software engineering and system programming for the efficient integration of the output of various tools. Details and further specification of the project can be discussed with Rebecca Dridan.