A system for recognition of named entities in Greek

Boutsis, S; Demiros, I; Giouli, V; Liakata, M; Papageorgiou, H; Piperidis, S

dc.contributor.author	Boutsis, S	en
dc.contributor.author	Demiros, I	en
dc.contributor.author	Giouli, V	en
dc.contributor.author	Liakata, M	en
dc.contributor.author	Papageorgiou, H	en
dc.contributor.author	Piperidis, S	en
dc.date.accessioned	2014-03-01T01:49:45Z
dc.date.available	2014-03-01T01:49:45Z
dc.date.issued	2000	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25900
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.title	A system for recognition of named entities in Greek	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	2000	en
heal.abstract	In this paper, we describe work in progress for the development of a Greek named entity recognizer. The system aims at information extraction applications where large scale text processing is needed. Speed of analysis, system robustness, and results accuracy have been the basic guidelines for the system's design. Pattern matching techniques have been implemented on top of an existing automated pipeline for Greek text processing and the resulting system depends on non-recursive regular expressions in order to capture different types of named entities. For development and testing purposes, we collected a corpus of financial texts from several web sources and manually annotated part of it. Overall precision and recall are 86% and 81 % respectively.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	NATURAL LANGUAGE PROCESSING-NLP 2000, PROCEEDINGS	en
heal.bookName	LECTURE NOTES IN ARTIFICIAL INTELLIGENCE	en
dc.identifier.isi	ISI:000170202300039	en
dc.identifier.volume	1835	en
dc.identifier.spage	424	en
dc.identifier.epage	435	en