Abstract
The WISE 2013 conference proposed a challenge (T1 Track) in which teams must label entities within plain texts based on Wikilinks dataset which comprises 40 million mentions over 3 million existed entities. This paper describe a straightforward two-fold unsupervised strategy to extract and tag entities, aiming to achieve accurate results in the identification of proper nouns and concrete concepts, regardless the domain. The proposed solution is based on a pipeline of text processing modules that includes a lexical parser. The solution labelled 8824 texts, and the results achieved satisfying precision measures.
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References
Ruiz-Casado, M., Alfonseca, E., Okumura, M., Castells, P.: Information Extraction and Semantic Annotation of Wikipedia. In: Proceeding of the 2008 Conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge, June 16, pp. 145–169 (2008)
Shaalan, K., Raza, H.: NERA: Named Entity Recognition for Arabic. J. Am. Soc. Inf. Sci. Technol. 60(8), 1652–1663 (2009)
Singh, S., Subramanya, A., Pereira, F., McCallum, A.: Wikilinks: A Large-scale Cross-Document Coreference Corpus Labeled via Links to Wikipedia. CMPSCI Technical Report, UM-CS-2012-015, University of Massachusetts Amherst (2012)
Ratinov, L., Roth, D., Downey, D., Anderson, M.: Local and Global Algorithms for Disambiguation to Wikipedia. Computational Linguistics 1, 1375–1384 (2011)
Bunescu, R., Pasca, M.: Using Encyclopedic Knowledge for Named Entity Disambiguation. In: Proceedings of EACL, vol. 6, pp. 9–16. ACL (2006)
Cardie, C.: Empirical Methods in Information Extraction. AI Magazine 18(4), 65–79 (1997)
Marcus, M.P., Beatrice, S., Marcinkiewicz, M.A.: Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics 19, 313–330 (1994)
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© 2013 Springer-Verlag Berlin Heidelberg
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Abreu, C. et al. (2013). Entity Extraction within Plain-Text Collections WISE 2013 Challenge - T1: Entity Linking Track. In: Lin, X., Manolopoulos, Y., Srivastava, D., Huang, G. (eds) Web Information Systems Engineering – WISE 2013. WISE 2013. Lecture Notes in Computer Science, vol 8180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41230-1_42
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DOI: https://doi.org/10.1007/978-3-642-41230-1_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41229-5
Online ISBN: 978-3-642-41230-1
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