We show how several novel tools in logicprogramming for AI (namely, continuation based linear and timeless assumptions, and datalog grammars) can assist us in producing terse treatments of difficult language processi...
详细信息
We show how several novel tools in logicprogramming for AI (namely, continuation based linear and timeless assumptions, and datalog grammars) can assist us in producing terse treatments of difficult language processing phenomena. As a proof of concept, we present a concise parser for datalog grammars (logic grammars where strings are represented with numbered word boundaries rather than as lists of words), that uses assumptions and a combination of left-corner parsing and charting. We then study two test cases of this parser's application: complete constituent coordination, and error diagnosis and correction.
We present a logicprogramming parsing methodology which we believe especially interesting for understanding implicit human-language structures. It records parsing state constituents through linear assumptions to be c...
详细信息
We show how two novel tools in logicprogramming for AI (namely, continuation-based linear and timeless assumptions, and Datalog grammars) can assist us in producing terse treatments of difficult language processing p...
详细信息
We show how two novel tools in logicprogramming for AI (namely, continuation-based linear and timeless assumptions, and Datalog grammars) can assist us in producing terse treatments of difficult language processing phenomena. As a proof of concept, we present a concise parser for Datalog grammars (logic grammars where strings are represented with numbered word boundaries rather than as lists of words) that uses assumptions and a combination of left-corner parsing and charting. We then study two test cases of this parser's application: complete constituent coordination, and error diagnosis and correction.
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