K. Voll, Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada
T. Yeh, Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada
V. Dahl, Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada
Abstract: We show how several novel tools in logic programming 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.
Index Terms:
logic programming; DATALOG; grammars; theorem proving; assumptive logic programming methodology; AI; continuation based linear assumptions; timeless assumptions; datalog grammars; terse treatments; language processing phenomena; proof of concept; concise parser; logic grammars; numbered word boundaries; left-corner parsing; charting; test cases; constituent coordination; error diagnosis; error correction
Citation:
K. Voll, T. Yeh, V. Dahl, "An assumptive logic programming methodology for parsing," ictai, pp.0011, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000