This paper describes an inductive logic programming learning method designed to acquire from a corpus specific Noun-Verb (N-V) pairs---relevant in information retrieval applications to perform index expansion---in order to build up semantic lexicons based on Pustejovsky's generative lexicon (GL) principles (Pustejovsky, 1995). In one of the components of this lexical model, called the qualia structure, words are described in terms of semantic roles. For example, the telic role indicates the purpose or function of an item (cut for knife), the agentive role its creation mode (build for house), etc. The qualia structure of a noun is mainly made up of verbal associations, encoding relational information. The learning method enables us to automatically extract, from a morphosyntactically and semantically tagged corpus, N-V pairs whose elements are linked by one of the semantic relations defined in the qualia structure in GL. It also infers rules explaining what in the surrounding context distinguishes such pairs from others also found in sentences of the corpus but which are not relevant. Stress is put here on the learning efficiency that is required to be able to deal with all the available contextual information, and to produce linguistically meaningful rules.

This paper presents a corpus-based method for extracting semantic relations between words. The method is based on two sequential procedures. First, it automatically classifies syntactic dependencies according to their selection restrictions. Those dependencies that require the same selection restrictions are put together into the same semantic group. Then, interpretation rules are applied on the classified syntactic dependencies, in order to learn the specific semantic relations underlying syntactically related words.

This paper describes the implementation and results of a machine learning method, developed within the inductive logic programming (ILP) framework (Muggleton and De-Raedt, 1994), to automatically extract, from a corpus tagged with parts of speech (POS) and semantic classes, noun-verb pairs whose components are bound by one of the relations defined in the qualia structure in the Generative Lexicon (Pustejovsky,1995).

Morphological information is useful for parsing, lemmatization, and in