dc.creator | Troyano Jiménez, José Antonio | es |
dc.creator | Díaz Madrigal, Víctor Jesús | es |
dc.creator | Enríquez de Salamanca Ros, Fernando | es |
dc.creator | Romero Moreno, Luisa María | es |
dc.date.accessioned | 2020-08-03T07:23:20Z | |
dc.date.available | 2020-08-03T07:23:20Z | |
dc.date.issued | 2004 | |
dc.identifier.citation | Troyano Jiménez, J.A., Díaz Madrigal, V.J., Enríquez de Salamanca Ros, F. y Romero Moreno, L.M. (2004). Improving the Performance of a Named Entity Extractor by Applying a Stacking Scheme. En IBERAMIA 2004: 9th Ibero-American Conference on Artificial Intelligence (295-304), Puebla, México: Springer. | |
dc.identifier.isbn | 978-3-540-23806-5 | es |
dc.identifier.issn | 0302-9743 | es |
dc.identifier.uri | https://hdl.handle.net/11441/100067 | |
dc.description.abstract | In this paper we investigate the way of improving the performance
of a Named Entity Extraction (NEE) system by applying machine
learning techniques and corpus transformation. The main resources used
in our experiments are the publicly available tagger TnT and a corpus
of Spanish texts in which named entities occurrences are tagged with
BIO tags. We split the NEE task into two subtasks 1) Named Entity
Recognition (NER) that involves the identification of the group of words
that make up the name of an entity and 2) Named Entity Classification
(NEC) that determines the category of a named entity. We have focused
our work on the improvement of the NER task, generating four different
taggers with the same training corpus and combining them using a
stacking scheme. We improve the baseline of the NER task (Fβ=1 value
of 81.84) up to a value of 88.37. When a NEC module is added to the
NER system the performance of the whole NEE task is also improved.
A value of 70.47 is achieved from a baseline of 66.07. | es |
dc.format | application/pdf | es |
dc.format.extent | 10 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | IBERAMIA 2004: 9th Ibero-American Conference on Artificial Intelligence (2004), p 295-304 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Improving the Performance of a Named Entity Extractor by Applying a Stacking Scheme | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-540-30498-2_30 | es |
dc.identifier.doi | 10.1007/978-3-540-30498-2_30 | es |
dc.publication.initialPage | 295 | es |
dc.publication.endPage | 304 | es |
dc.eventtitle | IBERAMIA 2004: 9th Ibero-American Conference on Artificial Intelligence | es |
dc.eventinstitution | Puebla, México | es |
dc.relation.publicationplace | Berlin | es |
dc.identifier.sisius | 6513368 | es |