Designing and evaluating patterns for relation acquisition from texts with Caméléon

Pattern-based approaches for knowledge identification in texts assume that linguistic regularities always characterise the same kind of knowledge, such as semantic relations. In this paper, we report the experimental evaluation of a large set of patterns using an ontology enrichment tool: Caméléon. Results emphasize the strong influence of the corpus on pattern efficiency and on their meaning. This influence confirms two of the hypotheses that motivated to define Caméléon as a support used in a human-driven process: (1) patterns and relations must be adapted to each project; (2) human interpretation is required to decide how to report the pieces of knowledge identified with patterns in the ontology.