@inproceedings{wang-etal-2020-enhanced,
title = "Enhanced {U}niversal {D}ependency Parsing with Second-Order Inference and Mixture of Training Data",
author = "Wang, Xinyu and
Jiang, Yong and
Tu, Kewei",
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-1.22",
doi = "10.18653/v1/2020.iwpt-1.22",
pages = "215--220",
abstract = "This paper presents the system used in our submission to the \textit{IWPT 2020 Shared Task}. Our system is a graph-based parser with second-order inference. For the low-resource Tamil corpora, we specially mixed the training data of Tamil with other languages and significantly improved the performance of Tamil. Due to our misunderstanding of the submission requirements, we submitted graphs that are not connected, which makes our system only rank \textbf{6th} over 10 teams. However, after we fixed this problem, our system is 0.6 ELAS higher than the team that ranked \textbf{1st} in the official results.",
}
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%0 Conference Proceedings
%T Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Data
%A Wang, Xinyu
%A Jiang, Yong
%A Tu, Kewei
%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 wang-etal-2020-enhanced
%X This paper presents the system used in our submission to the IWPT 2020 Shared Task. Our system is a graph-based parser with second-order inference. For the low-resource Tamil corpora, we specially mixed the training data of Tamil with other languages and significantly improved the performance of Tamil. Due to our misunderstanding of the submission requirements, we submitted graphs that are not connected, which makes our system only rank 6th over 10 teams. However, after we fixed this problem, our system is 0.6 ELAS higher than the team that ranked 1st in the official results.
%R 10.18653/v1/2020.iwpt-1.22
%U https://aclanthology.org/2020.iwpt-1.22
%U https://doi.org/10.18653/v1/2020.iwpt-1.22
%P 215-220
Markdown (Informal)
[Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Data](https://aclanthology.org/2020.iwpt-1.22) (Wang et al., IWPT 2020)
ACL