Paper: Hybrid Text Chunking

ACL ID W00-0737
Title Hybrid Text Chunking
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2000

This paper proposes an error-driven HMM- based text chunk tagger with context-dependent lexicon. Compared with standard HMM-based tagger, this tagger incorporates more contextual information into a lexical entry. Moreover, an error-driven learning approach is adopted to de- crease the memory requirement by keeping only positive lexical entries and makes it possible to further incorporate more context-dependent lexical entries. Finally, memory-based learning is adopted to further improve the performance of the chunk tagger.