Advanced Relaxation for Cooperative Question Answering.
Farah Benamara, Patrick Saint‐Dizier · 2004
Advanced reasoning for Question Answering (QA) systems, as described in a recent roadmap (http://www-nlpir.nist.gov/projects/duc/papers/qa.Roadmappaper_v2.doc), raises new challenges since answers are not only directly extracted from written texts or structured databases but also constructed via several forms of reasoning in order to generate answer explanations and justifications. These systems require the integration of reasoning components operating over a variety of knowledge bases, encoding common sense knowledge as well as knowledge specific to a variety of domains by means, for example, of conceptual ontologies. These kinds of QA systems can be viewed as an enhancement, rather than a rival to retrieval based approaches. Integrating knowledge representation and reasoning mechanisms allow, for example, to respond to unanticipated questions and to resolve situations in which no answer is found in the data sources. Cooperative answering systems are typically designed to deal with such situations by providing useful and informative answers. These systems can e.g. identify and explain false presuppositions or various types of misunderstandings found in questions. Constraints relaxation in questions occur when the system cannot find any response. Intensional responses are provided instead of a large unstructured set of extensional answers. Cooperative answering systems can also provide summaries or conditional responses. An overview of these aspects is given in (Gaasterland et al, 94).