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.
Aussenac-Gilles, Nathalie, Jean Charlet & Chantal Reynaud
2020. Knowledge Engineering. In A Guided Tour of Artificial Intelligence Research, ► pp. 733 ff.
Quesada-Martínez, Manuel, Jesualdo Tomás Fernández-Breis, Robert Stevens & Nathalie Aussenac-Gilles
2015. OntoEnrich: A Platform for the Lexical Analysis of Ontologies. In Knowledge Engineering and Knowledge Management [Lecture Notes in Computer Science, 8982], ► pp. 172 ff.
2013. A Terminology Indexing Based on Heuristics Using Linguistic Resources for Medical Textual Corpus. In Advances in Intelligent Analysis of Medical Data and Decision Support Systems [Studies in Computational Intelligence, 473], ► pp. 213 ff.
Mela, Augusta, Mathieu Roche & Mohamed El Amine Bekhtaoui
2012. Lexical Knowledge Acquisition Using Spontaneous Descriptions in Texts. In Natural Language Processing and Information Systems [Lecture Notes in Computer Science, 7337], ► pp. 366 ff.
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