Abstract
Pattern-based approaches for knowledge identification in texts assume that linguistic regularities always characterise the same kind of knowledge, such as semantic relations. We report the experimental evaluation of a large set of patterns using an ontology enrichment tool: CAMÉLÉON. Results underline the strong corpus influence on the patterns efficiency and on their meaning. This influence confirms two of the hypotheses that motivated to define CAMÉLÉON as a support used in a supervised process: (1) patterns and relations must be adapted to each project; (2) human interpretation is required to decide how to report in the ontology the pieces of knowledge identified with patterns. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Aussenac-Gilles, N., & Jacques, M. P. (2006). Designing and evaluating patterns for ontology enrichment from texts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4248 LNAI, pp. 158–165). Springer Verlag. https://doi.org/10.1007/11891451_16
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