Paper: Shallow Parsing By Inferencing With Classifiers

ACL ID W00-0721
Title Shallow Parsing By Inferencing With Classifiers
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2000
Authors

We study the problem of identifying phrase structure. We formalize it as the problem of combining the outcomes of several different clas- sifiers in a way that provides a coherent in- ference that satisfies some constraints, and de- velop two general approaches for it. The first is a Markovian approach that extends stan- dard HMMs to allow the use of a rich obser- vations structure and of general classifiers to model state-observation dependencies. The sec- ond is an extension of constraint satisfaction for- malisms. We also develop efficient algorithms under both models and study them experimen- tally in the context of shallow parsing. 1 1 Identifying Phrase Structure The problem of identifying phrase structure can be formalized as follows. Given an input string O =< ol, 02,..., On >, a p...