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.- Anthology ID:
- P17-2107
- Volume:
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- Month:
- July
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Regina Barzilay, Min-Yen Kan
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 679–684
- Language:
- URL:
- https://aclanthology.org/P17-2107
- DOI:
- 10.18653/v1/P17-2107
- Cite (ACL):
- Željko Agić and Natalie Schluter. 2017. How (not) to train a dependency parser: The curious case of jackknifing part-of-speech taggers. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 679–684, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- How (not) to train a dependency parser: The curious case of jackknifing part-of-speech taggers (Agić & Schluter, ACL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/P17-2107.pdf
- Data
- Universal Dependencies