Abstract
We present the contribution of the ONLP lab at the Open University of Israel to the CONLL 2018 UD SHARED TASK on MULTILINGUAL PARSING FROM RAW TEXT TO UNIVERSAL DEPENDENCIES. Our contribution is based on a transition-based parser called yap: yet another parser which includes a standalone morphological model, a standalone dependency model, and a joint morphosyntactic model. In the task we used yap's standalone dependency parser to parse input morphologically disambiguated by UDPipe, and obtained the official score of 58.35 LAS. In a follow up investigation we use yap to show how the incorporation of morphological and lexical resources may improve the performance of end-to-end raw-to-dependencies parsing in the case of a morphologically-rich and low-resource language, Modern Hebrew. Our results on Hebrew underscore the importance of CoNLL-UL, a UD-compatible standard for accessing external lexical resources, for enhancing end-to-end UD parsing, in particular for morphologically rich and low-resource languages. We thus encourage the community to create, convert, or make available more such lexica.
Original language | English |
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Title of host publication | CoNLL 2018 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2018 Shared Task |
Subtitle of host publication | Multilingual Parsing from Raw Text to Universal Dependencies |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 208-215 |
Number of pages | 8 |
ISBN (Electronic) | 9781948087827 |
DOIs | |
State | Published - 2018 |
Event | 2018 SIGNLL Conference on Computational Natural Language Learning, CoNLL Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, CoNLL 2018 - Brussels, Belgium Duration: 31 Oct 2018 → 1 Nov 2018 |
Publication series
Name | CoNLL 2018 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies |
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Conference
Conference | 2018 SIGNLL Conference on Computational Natural Language Learning, CoNLL Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, CoNLL 2018 |
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Country/Territory | Belgium |
City | Brussels |
Period | 31/10/18 → 1/11/18 |
Bibliographical note
Publisher Copyright:© 2018 Association for Computational Linguistics