Named Entity Extraction with Conjunction Disambiguation

Paweł Mazur, Robert Dale


Abstract
The recognition of named entities is now a well-developed area, with a range of symbolic and machine learning techniques that deliver high accuracy extraction and categorisation of a variety of entity types. However, there are still some named entity phenomena that present problems for existing techniques; in particular, relatively little work has explored the disambiguation of conjunctions appearing in candidate named entity strings. We demonstrate that there are in fact four distinct uses of conjunctions in the context of named entities; we present some experiments using machine-learned classifiers to disambiguate the different uses of the conjunction, with 85% of test examples being correctly classified.
Anthology ID:
L06-1284
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Editors:
Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/473_pdf.pdf
DOI:
Bibkey:
Cite (ACL):
Paweł Mazur and Robert Dale. 2006. Named Entity Extraction with Conjunction Disambiguation. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
Named Entity Extraction with Conjunction Disambiguation (Mazur & Dale, LREC 2006)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/473_pdf.pdf