LREC 2006 - Proceedings sorted by papers

Title	Named Entity Extraction with Conjunction Disambiguation
Authors	P. Mazur, R. 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.
Keywords	Information Extraction, Named Entity Recognition, Conjunction Disambiguation
Full paper	Named Entity Extraction with Conjunction Disambiguation

Title

Named Entity Extraction with Conjunction Disambiguation

Authors

P. Mazur, R. 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.

Keywords

Information Extraction, Named Entity Recognition, Conjunction Disambiguation

Full paper

Named Entity Extraction with Conjunction Disambiguation