Paper: SEXTANT: Exploring Unexplored Contexts For Semantic Extraction From Syntactic Analysis

ACL ID P92-1052
Title SEXTANT: Exploring Unexplored Contexts For Semantic Extraction From Syntactic Analysis
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1992
Authors

For a very long time, it has been con- sidered that the only way of automati- cally extracting similar groups of words from a text collection for which no se- mantic information exists is to use docu- ment co-occurrence data. But, with ro- bust syntactic parsers that are becom- ing more frequently available, syntacti- cally recognizable phenomena about word usage can be confidently noted in large collections of texts. We present here a new system called SEXTANT which uses these parsers and the finer-grained con- texts they produce to judge word similar- ity. BACKGROUND Many machine-based approaches to term sim- ilarity, such as found in TItUMP (Jacobs and Zernick 1988) and FERRET (Mauldin 1991), can be characterized as knowledge-rich in that they presuppose that known lexical items possess...