@inproceedings{chiruzzo-wonsever-2020-statistical,
title = "Statistical Deep Parsing for {S}panish Using Neural Networks",
author = "Chiruzzo, Luis and
Wonsever, Dina",
editor = "Bouma, Gosse and
Matsumoto, Yuji and
Oepen, Stephan and
Sagae, Kenji and
Seddah, Djam{\'e} and
Sun, Weiwei and
S{\o}gaard, Anders and
Tsarfaty, Reut and
Zeman, Dan",
booktitle = "Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.iwpt-1.14",
doi = "10.18653/v1/2020.iwpt-1.14",
pages = "132--144",
abstract = "This paper presents the development of a deep parser for Spanish that uses a HPSG grammar and returns trees that contain both syntactic and semantic information. The parsing process uses a top-down approach implemented using LSTM neural networks, and achieves good performance results in terms of syntactic constituency and dependency metrics, and also SRL. We describe the grammar, corpus and implementation of the parser. Our process outperforms a CKY baseline and other Spanish parsers in terms of global metrics and also for some specific Spanish phenomena, such as clitics reduplication and relative referents.",
}
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%0 Conference Proceedings
%T Statistical Deep Parsing for Spanish Using Neural Networks
%A Chiruzzo, Luis
%A Wonsever, Dina
%Y Bouma, Gosse
%Y Matsumoto, Yuji
%Y Oepen, Stephan
%Y Sagae, Kenji
%Y Seddah, Djamé
%Y Sun, Weiwei
%Y Søgaard, Anders
%Y Tsarfaty, Reut
%Y Zeman, Dan
%S Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F chiruzzo-wonsever-2020-statistical
%X This paper presents the development of a deep parser for Spanish that uses a HPSG grammar and returns trees that contain both syntactic and semantic information. The parsing process uses a top-down approach implemented using LSTM neural networks, and achieves good performance results in terms of syntactic constituency and dependency metrics, and also SRL. We describe the grammar, corpus and implementation of the parser. Our process outperforms a CKY baseline and other Spanish parsers in terms of global metrics and also for some specific Spanish phenomena, such as clitics reduplication and relative referents.
%R 10.18653/v1/2020.iwpt-1.14
%U https://aclanthology.org/2020.iwpt-1.14
%U https://doi.org/10.18653/v1/2020.iwpt-1.14
%P 132-144
Markdown (Informal)
[Statistical Deep Parsing for Spanish Using Neural Networks](https://aclanthology.org/2020.iwpt-1.14) (Chiruzzo & Wonsever, IWPT 2020)
ACL
- Luis Chiruzzo and Dina Wonsever. 2020. Statistical Deep Parsing for Spanish Using Neural Networks. In Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies, pages 132–144, Online. Association for Computational Linguistics.