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Combinatory categorial grammar (CCG) is a grammar formalism used for naturallanguage parsing. CCG assigns structured lexical categories to words and uses asmall set of combinatory rules to combine these categories to parse a sentence.In this work we propose and implement a new approach to CCG parsing that relieson a prominent knowledge representation formalism, answer set programming (ASP)- a declarative programming paradigm. We formulate the task of CCG parsing as aplanning problem and use an ASP computational tool to compute solutions thatcorrespond to valid parses. Compared to other approaches, there is no need toimplement a specific parsing algorithm using such a declarative method. Ourapproach aims at producing all semantically distinct parse trees for a givensentence. From this goal, normalization and efficiency issues arise, and wedeal with them by combining and extending existing strategies. We haveimplemented a CCG parsing tool kit - AspCcgTk - that uses ASP as its maincomputational means. The C&C supertagger can be used as a preprocessor withinAspCcgTk, which allows us to achieve wide-coverage natural language parsing.

Parsing Combinatory Categorial Grammar with Answer Set Programming: Preliminary Report