How (not) to train a dependency parser: The curious case of jackknifing part-of-speech taggers
- Zeljko Agic,
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 679-684 (6 pages)Publication milestones
- Published - 2017
Publication status
Published - 2017
Publisher
Association for Computational Linguistics, United StatesISBN (Electronic)
978-1-945626-76-0Publication IDs
- Scopus: 85040607451
Host publication title
Proceedings of the 55th Annual Meeting of the Association for Computational LinguisticsAbstract
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
Accepted author manuscript, 573.57 KB
Related Event
Title
The 55th Annual Meeting of the Association for Computational Linguistics
Event type
ConferenceLinks
Degree of recognition
International eventDate
30/07/2016 - 04/08/2017Location
VancouverCanada
