Taxonomy induction based on a collaboratively built knowledge repository

Authors:
Simone Paolo Ponzetto;Michael Strube
Affiliations:
Institut für Computerlinguistik, Heidelberg University, Heidelberg, Germany;Heidelberg Institute for Theoretical Studies gGmbH, Natural Language Processing Group, Heidelberg, Germany
Venue:
Artificial Intelligence
Year:
2011

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Abstract

The category system in Wikipedia can be taken as a conceptual network. We label the semantic relations between categories using methods based on connectivity in the network and lexico-syntactic matching. The result is a large scale taxonomy. For evaluation we propose a method which (1) manually determines the quality of our taxonomy, and (2) automatically compares its coverage with ResearchCyc, one of the largest manually created ontologies, and the lexical database WordNet. Additionally, we perform an extrinsic evaluation by computing semantic similarity between words in benchmarking datasets. The results show that the taxonomy compares favorably in quality and coverage with broad-coverage manually created resources.