How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations?

Abstract. This paper describes methods using Natural Language Processing ap-proaches to extract and validate induced syntactic relations (here restricted to the Verb-Object relation). These methods use a syntactic parser and a semantic close-ness measure to extract such relations. Then, their validation is based on two dif-ferent techniques: A Web Validation system on one part, then a Semantic-Vector-based approach, and finally different combinations of both techniques in order to rank induced Verb-Object relations. The Semantic Vector approach is a Roget-based method which computes a syntactic relation as a vector. Web Validation uses a search engine to determine the relevance of a syntactic relation according to its popularity. An experimental protocol is set up to judge automatically the relevance of the sorted induced relations. We finally apply our approach on a French corpus of news by using ROC Curves to evaluate the results