Paper: Experiments with Learning Parsing Heuristics

ACL ID P98-1048
Title Experiments with Learning Parsing Heuristics
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1998

Any large language processing software relies in its operation on heuristic decisions concerning the strategy of processing. These decisions are usually "hard-wired" into the software in the form of hand- crafted heuristic rules, independent of the nature of the processed texts. We propose an alternative, adaptive approach in which machine learning techniques learn the rules from examples of sentences in each class. We have experimented with a variety of learning techniques on a representative in- stance of this problem within the realm of parsing. Our approach lead to the discovery of new heuristics that perform significantly better than the current hand-crafted heuris- tic. We discuss the entire cycle of applica- tion of machine learning and suggest a methodology for the use of machine l...