Year: 2018
Type: conference-paper
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 transitionbased 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 UD-Pipe, 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.
Source: Proceedings of the
DOI: 10.18653/v1/k18-2021
Authors: Amit Seker, Amir More, Reut Tsarfaty
Institution: Open University of Israel
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2899045532