@inproceedings{na-min-2020-jbnu,
title = "{JBNU} at {MRP} 2020: {AMR} Parsing Using a Joint State Model for Graph-Sequence Iterative Inference",
author = "Na, Seung-Hoon and
Min, Jinwoo",
editor = "Oepen, Stephan and
Abend, Omri and
Abzianidze, Lasha and
Bos, Johan and
Haji{\v{c}}, Jan and
Hershcovich, Daniel and
Li, Bin and
O'Gorman, Tim and
Xue, Nianwen and
Zeman, Daniel",
booktitle = "Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.conll-shared.8",
doi = "10.18653/v1/2020.conll-shared.8",
pages = "83--87",
abstract = "This paper describes the Jeonbuk National University (JBNU) system for the 2020 shared task on Cross-Framework Meaning Representation Parsing at the Conference on Computational Natural Language Learning. Among the five frameworks, we address only the abstract meaning representation framework and propose a joint state model for the graph-sequence iterative inference of (Cai and Lam, 2020) for a simplified graph-sequence inference. In our joint state model, we update only a single joint state vector during the graph-sequence inference process instead of keeping the dual state vectors, and all other components are exactly the same as in (Cai and Lam, 2020).",
}
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%0 Conference Proceedings
%T JBNU at MRP 2020: AMR Parsing Using a Joint State Model for Graph-Sequence Iterative Inference
%A Na, Seung-Hoon
%A Min, Jinwoo
%Y Oepen, Stephan
%Y Abend, Omri
%Y Abzianidze, Lasha
%Y Bos, Johan
%Y Hajič, Jan
%Y Hershcovich, Daniel
%Y Li, Bin
%Y O’Gorman, Tim
%Y Xue, Nianwen
%Y Zeman, Daniel
%S Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F na-min-2020-jbnu
%X This paper describes the Jeonbuk National University (JBNU) system for the 2020 shared task on Cross-Framework Meaning Representation Parsing at the Conference on Computational Natural Language Learning. Among the five frameworks, we address only the abstract meaning representation framework and propose a joint state model for the graph-sequence iterative inference of (Cai and Lam, 2020) for a simplified graph-sequence inference. In our joint state model, we update only a single joint state vector during the graph-sequence inference process instead of keeping the dual state vectors, and all other components are exactly the same as in (Cai and Lam, 2020).
%R 10.18653/v1/2020.conll-shared.8
%U https://aclanthology.org/2020.conll-shared.8
%U https://doi.org/10.18653/v1/2020.conll-shared.8
%P 83-87
Markdown (Informal)
[JBNU at MRP 2020: AMR Parsing Using a Joint State Model for Graph-Sequence Iterative Inference](https://aclanthology.org/2020.conll-shared.8) (Na & Min, CoNLL 2020)
ACL