@inproceedings{aquino-de-leon-2020-parsing,
title = "Parsing in the absence of related languages: Evaluating low-resource dependency parsers on {T}agalog",
author = "Aquino, Angelina and
de Leon, Franz",
editor = "de Marneffe, Marie-Catherine and
de Lhoneux, Miryam and
Nivre, Joakim and
Schuster, Sebastian",
booktitle = "Proceedings of the Fourth Workshop on Universal Dependencies (UDW 2020)",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.udw-1.2/",
pages = "8--15",
abstract = "Cross-lingual and multilingual methods have been widely suggested as options for dependency parsing of low-resource languages; however, these typically require the use of annotated data in related high-resource languages. In this paper, we evaluate the performance of these methods versus monolingual parsing of Tagalog, an Austronesian language which shares little typological similarity with any existing high-resource languages. We show that a monolingual model developed on minimal target language data consistently outperforms all cross-lingual and multilingual models when no closely-related sources exist for a low-resource language."
}
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%0 Conference Proceedings
%T Parsing in the absence of related languages: Evaluating low-resource dependency parsers on Tagalog
%A Aquino, Angelina
%A de Leon, Franz
%Y de Marneffe, Marie-Catherine
%Y de Lhoneux, Miryam
%Y Nivre, Joakim
%Y Schuster, Sebastian
%S Proceedings of the Fourth Workshop on Universal Dependencies (UDW 2020)
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain (Online)
%F aquino-de-leon-2020-parsing
%X Cross-lingual and multilingual methods have been widely suggested as options for dependency parsing of low-resource languages; however, these typically require the use of annotated data in related high-resource languages. In this paper, we evaluate the performance of these methods versus monolingual parsing of Tagalog, an Austronesian language which shares little typological similarity with any existing high-resource languages. We show that a monolingual model developed on minimal target language data consistently outperforms all cross-lingual and multilingual models when no closely-related sources exist for a low-resource language.
%U https://aclanthology.org/2020.udw-1.2/
%P 8-15
Markdown (Informal)
[Parsing in the absence of related languages: Evaluating low-resource dependency parsers on Tagalog](https://aclanthology.org/2020.udw-1.2/) (Aquino & de Leon, UDW 2020)
ACL