Multilingual Fine-Grained Entity Typing

M.G.J. van Erp; P.T.J.M. Vossen

doi:10.1007/978-3-319-59888-8_23

Multilingual Fine-Grained Entity Typing

M.G.J. van Erp
, P.T.J.M. Vossen

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

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Abstract

Many entity recognition approaches classify recognised entities into a limited set of coarse-grained entity types. However, for deeper natural language analysis and end-user tasks, fine-grained entity types are more useful. For example, while standard named entity recognition may determine that an entity is a person knowing whether that entity is a politician or an actor is important for determining whether, in a subsequent relation extraction task, a relation should be acts or governs. Currently, fine-grained entity typing has only been investigated for English. In this paper, we present a fine-grained entity typing system for Dutch and Spanish using training data extracted from Wikipedia and DBpedia. Our system achieves comparable performance to English with an F1 measure of .90 on over 40 types for both Dutch and Spanish.

Original language	English
Title of host publication	Language, Data, and Knowledge
Subtitle of host publication	First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings
Editors	Jorge Gracia, Francis Bond, John P. McCrae, Paul Buitelaar, Christian Chiarcos, Sebastian Hellmann
Publisher	Springer
Pages	262-275
Number of pages	14
ISBN (Electronic)	9783319598888
ISBN (Print)	9783319598871
DOIs	https://doi.org/10.1007/978-3-319-59888-8_23
Publication status	Published - 2017

Publication series

Name	Lecture Notes in Computer Science (subseries Lecture Notes in Artificial Intelligence)
Publisher	Springer Verlag
Volume	10318 (LNAI)
ISSN (Print)	0302-9743

Funding

The research for this paper was made possible by the CLARIAH-CORE project financed by NWO.

Funders
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

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10.1007/978-3-319-59888-8_23

Multilingual Fine-Grained Entity TypingFinal published version, 418 KBLicence: Article 25fa Dutch Copyright Act

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van Erp, M. G. J., & Vossen, P. T. J. M. (2017). Multilingual Fine-Grained Entity Typing. In J. Gracia, F. Bond, J. P. McCrae, P. Buitelaar, C. Chiarcos, & S. Hellmann (Eds.), Language, Data, and Knowledge: First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings (pp. 262-275). (Lecture Notes in Computer Science (subseries Lecture Notes in Artificial Intelligence); Vol. 10318 (LNAI)). Springer. https://doi.org/10.1007/978-3-319-59888-8_23

van Erp, M.G.J. ; Vossen, P.T.J.M. / Multilingual Fine-Grained Entity Typing. Language, Data, and Knowledge: First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings. editor / Jorge Gracia ; Francis Bond ; John P. McCrae ; Paul Buitelaar ; Christian Chiarcos ; Sebastian Hellmann. Springer, 2017. pp. 262-275 (Lecture Notes in Computer Science (subseries Lecture Notes in Artificial Intelligence)).

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van Erp, MGJ & Vossen, PTJM 2017, Multilingual Fine-Grained Entity Typing. in J Gracia, F Bond, JP McCrae, P Buitelaar, C Chiarcos & S Hellmann (eds), Language, Data, and Knowledge: First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings. Lecture Notes in Computer Science (subseries Lecture Notes in Artificial Intelligence), vol. 10318 (LNAI), Springer, pp. 262-275. https://doi.org/10.1007/978-3-319-59888-8_23

Multilingual Fine-Grained Entity Typing. / van Erp, M.G.J.; Vossen, P.T.J.M.
Language, Data, and Knowledge: First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings. ed. / Jorge Gracia; Francis Bond; John P. McCrae; Paul Buitelaar; Christian Chiarcos; Sebastian Hellmann. Springer, 2017. p. 262-275 (Lecture Notes in Computer Science (subseries Lecture Notes in Artificial Intelligence); Vol. 10318 (LNAI)).

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

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AB - Many entity recognition approaches classify recognised entities into a limited set of coarse-grained entity types. However, for deeper natural language analysis and end-user tasks, fine-grained entity types are more useful. For example, while standard named entity recognition may determine that an entity is a person knowing whether that entity is a politician or an actor is important for determining whether, in a subsequent relation extraction task, a relation should be acts or governs. Currently, fine-grained entity typing has only been investigated for English. In this paper, we present a fine-grained entity typing system for Dutch and Spanish using training data extracted from Wikipedia and DBpedia. Our system achieves comparable performance to English with an F1 measure of .90 on over 40 types for both Dutch and Spanish.

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van Erp MGJ, Vossen PTJM. Multilingual Fine-Grained Entity Typing. In Gracia J, Bond F, McCrae JP, Buitelaar P, Chiarcos C, Hellmann S, editors, Language, Data, and Knowledge: First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings. Springer. 2017. p. 262-275. (Lecture Notes in Computer Science (subseries Lecture Notes in Artificial Intelligence)). Epub 2017 May 27. doi: 10.1007/978-3-319-59888-8_23

Multilingual Fine-Grained Entity Typing

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