PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Learning Deterministic Context Free Grammars: The Omphalos Competition
Alexander Clark
Machine Learning 2006.

Abstract

This paper describes the winning entry to the Omphalos context free grammar learning competition. We describe a context-free grammatical inference algorithm operating on positive data only, which integrates an information theoretic constituent likelihood measure together with more traditional heuristics based on substitutability and frequency. The competition is discussed from the perspective of a competitor. We discuss a class of deterministic grammars, the Non-terminally Separated (NTS) grammars, that have a property relied on by our algorithm, and consider the possibilities of extending the algorithm to larger classes of languages.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Theory & Algorithms
ID Code:2174
Deposited By:Alexander Clark
Deposited On:12 August 2006