Cross-lingual tagger evaluation without test data

Zeljko Agic; Barbara Plank; Anders Søgaard

Cross-lingual tagger evaluation without test data

Zeljko Agic, Barbara Plank, Anders Søgaard

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

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.

Originalsprog	Engelsk
Titel	Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics
Forlag	Association for Computational Linguistics
Publikationsdato	2017
Sider	248-253
ISBN (Elektronisk)	978-1-945626-35-7
Status	Udgivet - 2017
Begivenhed	The 15th Conference of the European Chapter of the Association for Computational Linguistics - Valencia, Spanien Varighed: 3 apr. 2017 → 7 apr. 2017 http://eacl2017.org/

Konference

Konference	The 15th Conference of the European Chapter of the Association for Computational Linguistics
Land/Område	Spanien
By	Valencia
Periode	03/04/2017 → 07/04/2017
Internetadresse	http://eacl2017.org/

Emneord

Cross-lingual POS tagging
Dictionary-based evaluation metrics
Accuracy prediction
System ranking
Low-resource languages assessment

Adgang til dokumentet

agic2017-cross.preprintAccepteret manuskript, 782 KB

http://aclweb.org/anthology/E/E17/E17-2040.pdf

Citationsformater

@inproceedings{a5d9cfb2048242da8ef2f5260f23e618,

title = "Cross-lingual tagger evaluation without test data",

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.",

keywords = "Cross-lingual POS tagging, Dictionary-based evaluation metrics, Accuracy prediction, System ranking, Low-resource languages assessment, Cross-lingual POS tagging, Dictionary-based evaluation metrics, Accuracy prediction, System ranking, Low-resource languages assessment",

author = "Zeljko Agic and Barbara Plank and Anders S{\o}gaard",

year = "2017",

language = "English",

pages = "248--253",

booktitle = "Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics",

publisher = "Association for Computational Linguistics",

address = "United States",

note = "The 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 ; Conference date: 03-04-2017 Through 07-04-2017",

url = "http://eacl2017.org/",

}

Agic, Z, Plank, B & Søgaard, A 2017, Cross-lingual tagger evaluation without test data. i Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, s. 248-253, The 15th Conference of the European Chapter of the Association for Computational Linguistics, Valencia, Spanien, 03/04/2017. <http://aclweb.org/anthology/E/E17/E17-2040.pdf>

Cross-lingual tagger evaluation without test data. / Agic, Zeljko; Plank, Barbara; Søgaard, Anders.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 2017. s. 248-253.

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - Cross-lingual tagger evaluation without test data

AU - Agic, Zeljko

AU - Plank, Barbara

AU - Søgaard, Anders

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Cross-lingual POS tagging

KW - Dictionary-based evaluation metrics

KW - Accuracy prediction

KW - System ranking

KW - Low-resource languages assessment

KW - Cross-lingual POS tagging

KW - Dictionary-based evaluation metrics

KW - Accuracy prediction

KW - System ranking

KW - Low-resource languages assessment

M3 - Article in proceedings

SP - 248

EP - 253

BT - Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics

PB - Association for Computational Linguistics

T2 - The 15th Conference of the European Chapter of the Association for Computational Linguistics

Y2 - 3 April 2017 through 7 April 2017

ER -

Cross-lingual tagger evaluation without test data

Abstract

Konference

Emneord

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Fingeraftryk

Citationsformater