Named Entity Recognition without Gazetteers

Named Entity Recognition without Gazetteers (1999)

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by Andrei Mikheev , Marc Moens , Claire Grover

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Datum	Value	Source
TITLE	Named Entity Recognition without Gazetteers	user correction - Legacy Corrections
AUTHOR NAME	Andrei Mikheev	SVM HeaderParse 0.1
AUTHOR AFFIL	HCRC Language Technology Group,; University of Edinburgh,	SVM HeaderParse 0.2
AUTHOR ADDR	2 Buccleuch Place, Edinburgh EH8 9LW, UK.	SVM HeaderParse 0.1
AUTHOR NAME	Marc Moens	SVM HeaderParse 0.1
AUTHOR AFFIL	HCRC Language Technology Group,; University of Edinburgh,	SVM HeaderParse 0.2
AUTHOR ADDR	2 Buccleuch Place, Edinburgh EH8 9LW, UK.	SVM HeaderParse 0.1
AUTHOR NAME	Claire Grover	SVM HeaderParse 0.1
AUTHOR AFFIL	HCRC Language Technology Group,; University of Edinburgh,	SVM HeaderParse 0.2
AUTHOR ADDR	2 Buccleuch Place, Edinburgh EH8 9LW, UK.	SVM HeaderParse 0.1
ABSTRACT	It is often claimed that Named Entity recognition systems need extensive gazetteers--lists of names of people, organisations, locations, and other named entities. Indeed, the compilation of such gazetteers is sometimes mentioned as a bottleneck in the design of Named Entity recognition systems. We report on a Named Entity recognition system which combines rule-based grammars with statistical (maximum entropy) models. We report on the system's performance with gazetteers of different types and different sizes, using test material from the MUC-7 competition. We show that, for the text type and task of this competition, it is sufficient to use relatively small gazetteers of well-known names, rather than large gazetteers of low-frequency names. We conclude with observations about the domain independence of the competition and of our experiments.	user correction - Legacy Corrections
YEAR	1999	user correction - Legacy Corrections
CITATIONS	9 found	ParsCit 1.0