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Zeitschrift für Sprachwissenschaft

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Eigennamenerkennung zwischen morphologischer Analyse und Part-of-Speech Tagging: ein automatentheoriebasierter Ansatz

Jörg Didakowski1 / Alexander Geyken2 / Thomas Hanneforth3

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Citation Information: Zeitschrift für Sprachwissenschaft. Volume 26, Issue 2, Pages 157–186, ISSN (Online) 1613-3706, ISSN (Print) 0721-9067, DOI: 10.1515/ZFS.2007.016, December 2007

Publication History

Received:
2007-02-02
Revised:
2007-06-12
Published Online:
2007-12-04

Abstract

Previous rule-based approaches for Named Entity Recognition (NER) in German base NER on Part-of-Speech tagged texts. We present a new approach where NER is situated between morphological analysis and Part-of-Speech Tagging and model the NER-grammar entirely with weighted finite state transducers (WFST). We show that NER strategies like the resolution of proper noun/common noun or company-name/family-name ambiguities can be formulated as a best path function of a WFST. The frequently used second pass resolution of coreferential Named Entities can be formulated as a re-assignment of appropriate weights. A prototypical NE recognition system built on the basis of WSFT and large lexical resources was tested on a manually annotated corpus of 65,000 tokens. The results show that our system compares in recall and precision to existing rule-based approaches.

Keywords: Named Entity Recognition; weighted finite state transducers; large lexical resources

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