Paper: Chunking Using Conditional Random Fields in Korean Texts

ACL ID I05-1014
Title Chunking Using Conditional Random Fields in Korean Texts
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2005
Authors

We give a detailed account of an algorithm for efficient tactical gener- ation from underspecified logical-form semantics, using a wide-coverage gram- mar and a corpus of real-world target utterances. Some earlier claims about chart realization are critically reviewed and corrected in the light of a series of practical experiments. As well as a set of algorithmic refinements, we present two novel techniques: the integration of subsumption-based local ambiguity factoring, and a procedure to selectively unpack the generation forest according to a probability distribution given by a conditional, discriminative model.