Named entity extraction with conjunction disambiguation

Pawel Mazur, Robert Dale

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

2 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationProceedings of the 5th Internationl Conference on Language Resources and Evaluation
EditorsNicoletta Calzolari
Place of PublicationGenoa, Italy
PublisherEuropean Language Resources Association
Pages1752-1755
Number of pages4
Publication statusPublished - 2006
EventInternationl Conference on Language Resources and Evaluation (5th : 2006) - Genoa, Italy
Duration: 22 May 200628 May 2006

Conference

ConferenceInternationl Conference on Language Resources and Evaluation (5th : 2006)
CityGenoa, Italy
Period22/05/0628/05/06

Fingerprint

Dive into the research topics of 'Named entity extraction with conjunction disambiguation'. Together they form a unique fingerprint.

Cite this