@inproceedings{straka-strakova-2019-ufal,
title = "{{\'U}FAL} {MRP}ipe at {MRP} 2019: {UDP}ipe Goes Semantic in the Meaning Representation Parsing Shared Task",
author = "Straka, Milan and
Strakov{\'a}, Jana",
editor = "Oepen, Stephan and
Abend, Omri and
Hajic, Jan and
Hershcovich, Daniel and
Kuhlmann, Marco and
O{'}Gorman, Tim and
Xue, Nianwen",
booktitle = "Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning",
month = nov,
year = "2019",
address = "Hong Kong",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/K19-2012",
doi = "10.18653/v1/K19-2012",
pages = "127--137",
abstract = "We present a system description of our contribution to the CoNLL 2019 shared task, CrossFramework Meaning Representation Parsing (MRP 2019). The proposed architecture is our first attempt towards a semantic parsing extension of the UDPipe 2.0, a lemmatization, POS tagging and dependency parsing pipeline. For the MRP 2019, which features five formally and linguistically different approaches to meaning representation (DM, PSD, EDS, UCCA and AMR), we propose a uniform, language and framework agnostic graph-tograph neural network architecture. Without any knowledge about the graph structure, and specifically without any linguistically or framework motivated features, our system implicitly models the meaning representation graphs. After fixing a human error (we used earlier incorrect version of provided test set analyses), our submission would score third in the competition evaluation. The source code of our system is available at \url{https://github.com/ufal/mrpipe-conll2019}.",
}
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%0 Conference Proceedings
%T ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared Task
%A Straka, Milan
%A Straková, Jana
%Y Oepen, Stephan
%Y Abend, Omri
%Y Hajic, Jan
%Y Hershcovich, Daniel
%Y Kuhlmann, Marco
%Y O’Gorman, Tim
%Y Xue, Nianwen
%S Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong
%F straka-strakova-2019-ufal
%X We present a system description of our contribution to the CoNLL 2019 shared task, CrossFramework Meaning Representation Parsing (MRP 2019). The proposed architecture is our first attempt towards a semantic parsing extension of the UDPipe 2.0, a lemmatization, POS tagging and dependency parsing pipeline. For the MRP 2019, which features five formally and linguistically different approaches to meaning representation (DM, PSD, EDS, UCCA and AMR), we propose a uniform, language and framework agnostic graph-tograph neural network architecture. Without any knowledge about the graph structure, and specifically without any linguistically or framework motivated features, our system implicitly models the meaning representation graphs. After fixing a human error (we used earlier incorrect version of provided test set analyses), our submission would score third in the competition evaluation. The source code of our system is available at https://github.com/ufal/mrpipe-conll2019.
%R 10.18653/v1/K19-2012
%U https://aclanthology.org/K19-2012
%U https://doi.org/10.18653/v1/K19-2012
%P 127-137
Markdown (Informal)
[ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared Task](https://aclanthology.org/K19-2012) (Straka & Straková, CoNLL 2019)
ACL