Paper: Local Context Templates For Chinese Constituent Boundary Prediction

ACL ID C00-2141
Title Local Context Templates For Chinese Constituent Boundary Prediction
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2000
Authors

in this paper, we proposed a shallow syntactic knowledge description: constituent boundary representation and its simple and efficient prediction algorithm, based on different local context templates learned fiom the annotated corpus. An open test on 2780 Chinese real text sentences showed the satisfying results: 94%(92%) precision for the words with multiple (single) boundary tag output. llt simplified the complex constituent levels in parse trees and only kept the boundary information of every word in different constituents. Then, we developed a simple and efficient constituent boundary prediction algorithm, based on different local context templates learned flom the annotated corpus. An open test on 2780 Chinese real text sentences showed the satisfying results: 94%(92%) precision for ...