Paper: Reducing Parsing Complexity By Intra-Sentence Segmentation Based On Maximum Entropy Model

ACL ID W00-1321
Title Reducing Parsing Complexity By Intra-Sentence Segmentation Based On Maximum Entropy Model
Venue 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora
Session Main Conference
Year 2000
Authors

Long sentence analysis has been a critical problem because of high complexity. This pa- per addresses the reduction of parsing com- plexity by intra-sentence segmentation, and presents maximum entropy model for deter- mining segmentation positions. The model features lexical contexts of segmentation posi- tions, giving a probability to each potential position. Segmentation coverage and accu- racy of the proposed method are 96% and 88% respectively. The parsing efficiency is im- proved by 77% in time and 71% in space.