Paper: Learning Parse And Translation Decisions From Examples With Rich Context

ACL ID P97-1062
Title Learning Parse And Translation Decisions From Examples With Rich Context
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1997
Authors

We present a knowledge and context-based system for parsing and translating natu- ral language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired un- der supervision to generate a determinis- tic shift-reduce parser in the form of a de- cision structure. It relies heavily on con- text, as encoded in features which describe the morphological, syntactic, semantic and other aspects of a given parse state.