  Combinatory categorial grammar (CCG) is a grammar formalism used for natural
language parsing. CCG assigns structured lexical categories to words and uses a
small 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 relies
on a prominent knowledge representation formalism, answer set programming (ASP)
- a declarative programming paradigm. We formulate the task of CCG parsing as a
planning problem and use an ASP computational tool to compute solutions that
correspond to valid parses. Compared to other approaches, there is no need to
implement a specific parsing algorithm using such a declarative method. Our
approach aims at producing all semantically distinct parse trees for a given
sentence. From this goal, normalization and efficiency issues arise, and we
deal with them by combining and extending existing strategies. We have
implemented a CCG parsing tool kit - AspCcgTk - that uses ASP as its main
computational means. The C&C supertagger can be used as a preprocessor within
AspCcgTk, which allows us to achieve wide-coverage natural language parsing.
