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Abstract The aim of this chapter is to explore modelling a more non-standard interaction between a human and a database. We try to equip the database with the capability of understanding queries in natural language and answering them in a more ‘intelligent’ manner than by mere yes/no factual answers. This capability of the database requires (at least) two components. First the database must possess a front-end logic module which can parse the natural language input I and translate it into a query (or update) Q1 in its own (logical) query language. Second, and in fact more difficult, it must cope with the logical patterns of human query and answer, which is logically more (non-monotonic) commonsense than ordinary query languages.
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Abstract The aim of this chapter is to explore modelling a more non-standard interaction between a human and a database. We try to equip the database with the capability of understanding queries in natural language and answering them in a more ‘intelligent’ manner than by mere yes/no factual answers. This capability of the database requires (at least) two components. First the database must possess a front-end logic module which can parse the natural language input I and translate it into a query (or update) Q1 in its own (logical) query language. Second, and in fact more difficult, it must cope with the logical patterns of human query and answer, which is logically more (non-monotonic) commonsense than ordinary query languages.
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