Cross-lingual tagger evaluation without test data

Zeljko Agic, Barbara Plank, Anders Søgaard

4 Citations (Scopus)

Abstract

We address the challenge of cross-lingual POS tagger evaluation in absence of manually annotated test data. We put forth and evaluate two dictionary-based metrics. On the tasks of accuracy prediction and system ranking, we reveal that these metrics are reliable enough to approximate test set-based evaluation, and at the same time lean enough to support assessment for truly low-resource languages.

Original languageEnglish
Title of host publicationProceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics : short papers
Number of pages6
Volume2
PublisherAssociation for Computational Linguistics
Publication date2017
Pages248-253
ISBN (Electronic)9781510838604
Publication statusPublished - 2017
Event15th Conference of the European Chapter of the Association for Computational Linguistics - Valencia, Spain
Duration: 3 Apr 20177 Apr 2017
Conference number: 15

Conference

Conference15th Conference of the European Chapter of the Association for Computational Linguistics
Number15
Country/TerritorySpain
CityValencia
Period03/04/201707/04/2017

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