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Ontology-based query processing for understanding intentions of indirect speech acts in natural-language question answering

In an attempt to develop a robust method for achieving natural-language question answering, we propose a method for ontology-based query processing to infer intentions from indirect speech acts that do not express the real intentions explicitly. In this method, the real intentions of the indirect speech act are classified into one of five intention classes such as 'refusal' and 'reversal'. Furthermore, we construct an ontology for intention transition, which is composed of concepts for events and their relations attributed with the above intention classes. In addition, we construct an ontology of objects for the targets of events – e.g. 'files' and 'figures', which also contains special relations such as 'exclusive'. Given the two above ontologies, an algorithm is proposed to infer users' actual intentions. This proposed method was tested with human subjects and a prototype system. The system successfully inferred the intentions for approximately 80% of the subjects' indirect speech acts.