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How (not) to train a dependency parser: The curious case of jackknifing part-of-speech taggers

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 679-684 (6 pages)

Publication milestones

  • Published - 2017

Publication status

Published - 2017

Publisher

Association for Computational Linguistics, United States

ISBN (Electronic)

978-1-945626-76-0

Publication IDs

  • Scopus: 85040607451

Host publication title

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics

Abstract

In dependency parsing, jackknifing taggers is indiscriminately used as a simple adaptation strategy. Here, we empirically evaluate when and how (not) to use jackknifing in parsing. On 26 languages, we reveal a preference that conflicts with, and surpasses the ubiquitous ten-folding. We show no clear benefits of tagging the training data in cross-lingual parsing.

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Citations
5
Captures
89

Access to documents

Related Event

Title

The 55th Annual Meeting of the Association for Computational Linguistics

Event type

Conference

Degree of recognition

International event

Date

30/07/2016 - 04/08/2017

Location

VancouverCanada