Working Notes of the IJCAI-95 Workshop on New Approaches to Learning for Natural Language Processing, pp.79-86, Montreal, Quebec, Canada, August 1995.
Paper ID: 47
Category: Inductive Logic Programming, Natural Language Learning, Learning for Semantic Parsing
This paper presents results from recent experiments with CHILL, a corpus-based parser acquisition system. CHILL treats grammar acquisition as the learning of search-control rules within a logic program. Unlike many current corpus-based approaches that use propositional or probabilistic learning algorithms, CHILL uses techniques from inductive logic programming (ILP) to learn relational representations. The reported experiments compare CHILL's performance to that of a more naive application of ILP to parser acquisition. The results show that ILP techniques, as employed in CHILL, are a viable alternative to propositional methods and that the control-rule framework is fundamental to CHILL's success.
