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dc.contributor.authorCatala Roig, Neus
dc.contributor.authorCastell Ariño, Núria
dc.contributor.authorMartín Muñoz, Mario
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2016-11-10T15:43:30Z
dc.date.available2016-11-10T15:43:30Z
dc.date.issued2000-11
dc.identifier.citationCatalà Roig, N., Castell, N., Martin, M. "Using ESSENCE for acquiring information extraction patterns". 2000.
dc.identifier.urihttp://hdl.handle.net/2117/96498
dc.description.abstractOne important issue when constructing Information Extraction systems is how to obtain the knowledge needed for identifying relevant information in a document. In most approaches to this issue, the human expert intervention is necessary in many steps of the acquisition process. In this paper we describe {sc Essence}, a new methodology that reduces significantly the need for human intervention. It is based on ELA, a new algorithm for acquiring information extraction patterns. The distinctive features of {sc Essence} and ELA are that 1) allow to automatically acquire IE patterns from unrestricted text corpus representative of the domain, due to 2) the ability of identifying surrounding context regularities for semantically relevant concept-words for the IE task by using non domain specific lexical knowledge tools and semantic relations from WordNet, and 3) restricting the human intervention to only the definition of the task and the validation and typification of the set of IE patterns obtained. The use of a general purpose ontology and syntactic tools of general application allows the easy portability of the methodology and reduces the expert effort. Results of the application of this methodology for acquiring extraction patterns in a MUC-like task are also shown.
dc.format.extent15 p.
dc.language.isoeng
dc.relation.ispartofseriesLSI-00-65-R
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.otherAcquiring information extraction patterns
dc.subject.otherESSENCE
dc.titleUsing ESSENCE for acquiring information extraction patterns
dc.typeExternal research report
dc.contributor.groupUniversitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
dc.contributor.groupUniversitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic
dc.rights.accessOpen Access
drac.iddocument1874987
dc.description.versionPostprint (published version)
upcommons.citation.authorCatalà Roig, N., Castell, N., Martin, M.
upcommons.citation.publishedtrue


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