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Evaluating Compound Splitting Extrinsically with Textual Entailment

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Evaluating Compound Splitting Extrinsically with Textual Entailment. / Jagfeld, Glorianna; Ziering, Patrick; van der Plas, Lonneke.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers),. Vol. 2 Stroudsburg, PA: Association for Computational Linguistics, 2017. p. 58-63.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Jagfeld, G, Ziering, P & van der Plas, L 2017, Evaluating Compound Splitting Extrinsically with Textual Entailment. in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers),. vol. 2, Association for Computational Linguistics, Stroudsburg, PA, pp. 58-63, Annual Meeting of the
Association for Computational Linguistics 2017, Vancouver, Canada, 30/07/17. https://doi.org/10.18653/v1/P17-2010

APA

Jagfeld, G., Ziering, P., & van der Plas, L. (2017). Evaluating Compound Splitting Extrinsically with Textual Entailment. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers), (Vol. 2, pp. 58-63). Association for Computational Linguistics. https://doi.org/10.18653/v1/P17-2010

Vancouver

Jagfeld G, Ziering P, van der Plas L. Evaluating Compound Splitting Extrinsically with Textual Entailment. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers),. Vol. 2. Stroudsburg, PA: Association for Computational Linguistics. 2017. p. 58-63 doi: 10.18653/v1/P17-2010

Author

Jagfeld, Glorianna ; Ziering, Patrick ; van der Plas, Lonneke. / Evaluating Compound Splitting Extrinsically with Textual Entailment. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers),. Vol. 2 Stroudsburg, PA : Association for Computational Linguistics, 2017. pp. 58-63

Bibtex

@inproceedings{f88538b774b644beac165736200a912f,
title = "Evaluating Compound Splitting Extrinsically with Textual Entailment",
abstract = "Traditionally, compound splitters are evaluated intrinsically on gold-standard data or extrinsically on the task of statistical machine translation. We explore a novel way for the extrinsic evaluation of compound splitters, namely recognizing textual entailment. Compound splitting has great potential for this novel task that is both transparent and well-defined. Moreover, we show that it addresses certain aspects that are either ignored in intrinsic evaluations or compensated for by taskinternal mechanisms in statistical machine translation. We show significant improvements using different compound splitting methods on a German textual entailment dataset.",
author = "Glorianna Jagfeld and Patrick Ziering and {van der Plas}, Lonneke",
year = "2017",
month = aug,
day = "4",
doi = "10.18653/v1/P17-2010",
language = "English",
isbn = "9781945626760",
volume = "2",
pages = "58--63",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers),",
publisher = "Association for Computational Linguistics",
note = "Annual Meeting of the<br/>Association for Computational Linguistics 2017, ACL ; Conference date: 30-07-2017 Through 04-08-2017",
url = "http://acl2017.org/",

}

RIS

TY - GEN

T1 - Evaluating Compound Splitting Extrinsically with Textual Entailment

AU - Jagfeld, Glorianna

AU - Ziering, Patrick

AU - van der Plas, Lonneke

PY - 2017/8/4

Y1 - 2017/8/4

N2 - Traditionally, compound splitters are evaluated intrinsically on gold-standard data or extrinsically on the task of statistical machine translation. We explore a novel way for the extrinsic evaluation of compound splitters, namely recognizing textual entailment. Compound splitting has great potential for this novel task that is both transparent and well-defined. Moreover, we show that it addresses certain aspects that are either ignored in intrinsic evaluations or compensated for by taskinternal mechanisms in statistical machine translation. We show significant improvements using different compound splitting methods on a German textual entailment dataset.

AB - Traditionally, compound splitters are evaluated intrinsically on gold-standard data or extrinsically on the task of statistical machine translation. We explore a novel way for the extrinsic evaluation of compound splitters, namely recognizing textual entailment. Compound splitting has great potential for this novel task that is both transparent and well-defined. Moreover, we show that it addresses certain aspects that are either ignored in intrinsic evaluations or compensated for by taskinternal mechanisms in statistical machine translation. We show significant improvements using different compound splitting methods on a German textual entailment dataset.

U2 - 10.18653/v1/P17-2010

DO - 10.18653/v1/P17-2010

M3 - Conference contribution/Paper

SN - 9781945626760

VL - 2

SP - 58

EP - 63

BT - Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers),

PB - Association for Computational Linguistics

CY - Stroudsburg, PA

T2 - Annual Meeting of the<br/>Association for Computational Linguistics 2017

Y2 - 30 July 2017 through 4 August 2017

ER -