SEXTANT: Exploring Unexplored Contexts for Semantic Extraction from Syntactic Analysis

For a very long time, it has been considered that the only way of automatically extracting similar groups of words from a text collection for which no semantic information exists is to use document co-occurrence data. But, with robust syntactic parsers that are becoming more frequently available, syntactically 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 contexts they produce to judge word similarity. BACKGROUND Many machine-based approaches to term similarity, 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 Conceptual Dependence(CD)like descriptions. Such an approach necessitates a great amount of manual encoding of semantic information and suffers from the drawbacks of cost (in terms of initial coding, coherence checking...

• Type: Conference
• Year: 1992
• Where: ACL
• Authors: Gregory Grefenstette
• Keywords: ACL 1992, ACL 2007, Document Co-occurrence, Semantic, Semantic Information