2006 OntolPopFromTextualMentions

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Subject Headings: Ontology Population from Text Algorithm, Weakly-Supervised Algorithm.

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Abstract

In this paper we propose and investigate Ontology Population from Textual Mentions (OPTM), a sub-task of Ontology Population from text where we assume that mentions for several kinds of entities (e.g. PERSON, ORGANIZATION, LOCATION, GEOPOLITICAL_ENTITY) are already extracted from a document collection. On the one hand, OPTM simplifies the general Ontology Population task, limiting the input textual material; on the other hand, it introduces challenging extensions to Ontology Population restricted to named entities, being open to a wider spectrum of linguistic phenomena. We describe a manually created benchmark for OPTM and discuss several factors which determine the difficulty of the task.


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2006 OntolPopFromTextualMentionsManuela Speranza
Bernardo Magnini
Emanuele Pianta
Octavian Popescu
Ontology Population from Textual Mentions: Task Definition and Benchmarkhttp://tcc.itc.it/people/pianta/publications/olp2-2006-final.pdf