Paper: Exploiting Chunk-level Features to Improve Phrase Chunking

ACL ID D12-1051
Title Exploiting Chunk-level Features to Improve Phrase Chunking
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012
Authors

Most existing systems solved the phrase chunking task with the sequence labeling approaches, in which the chunk candidates cannot be treated as a whole during parsing process so that the chunk-level features cannot be exploited in a natural way. In this paper, we formulate phrase chunking as a joint segmentation and labeling task. We propose an efficient dynamic programming algorithm with pruning for decoding, which allows the direct use of the features describing the internal characteristics of chunk and the features capturing the correlations between adjacent chunks. A relaxed, online maximum margin training algorithm is used for learning. Within this framework, we explored a variety of effective feature representations for Chinese phrase chunking. The experimental re...