Abstract
This is a system description paper for the CUNI x-ling submission to the CoNLL 2018 UD Shared Task. We focused on parsing under-resourced languages, with no or little training data available. We employed a wide range of approaches, including simple word-based treebank translation, combination of delexicalized parsers, and exploitation of available morphological dictionaries, with a dedicated setup tailored to each of the languages. In the official evaluation, our submission was identified as the clear winner of the Low-resource languages category.
Cite
CITATION STYLE
Rosa, R., & Mareček, D. (2018). CUNI x-ling: Parsing under-resourced languages in CoNLL 2018 UD Shared Task. In CoNLL 2018 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies (pp. 187–196). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/K18-2019
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