Paper: A Corpus-Based Learning Technique For Building A Self-Extensible Parser

ACL ID C94-1073
Title A Corpus-Based Learning Technique For Building A Self-Extensible Parser
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1994
Authors

IIuman intervention and/or training corpora tagged with various kinds of information were often assumed in many natural language acquisition models. This assumption is a major source of inconsistencies, er- rors, and inefficiency in learning. In this paper, we explore the extent to which a parser may extend it- self without relying on extra input from the outside world. A learning technique called SEP is proposed and attached to the parser. The input to SEP is raw sentences, while the output is the knowledge that is missing in the parser. Since parsers and raw sentences are commonly available and no human intervention is needed in learning, SEP could make fully automatic large-scale acquisition more feasible.