@inproceedings{mulcaire-etal-2018-polyglot,
title = "Polyglot Semantic Role Labeling",
author = "Mulcaire, Phoebe and
Swayamdipta, Swabha and
Smith, Noah A.",
editor = "Gurevych, Iryna and
Miyao, Yusuke",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-2106",
doi = "10.18653/v1/P18-2106",
pages = "667--672",
abstract = "Previous approaches to multilingual semantic dependency parsing treat languages independently, without exploiting the similarities between semantic structures across languages. We experiment with a new approach where we combine resources from different languages in the CoNLL 2009 shared task to build a single polyglot semantic dependency parser. Notwithstanding the absence of parallel data, and the dissimilarity in annotations between languages, our approach results in improvement in parsing performance on several languages over a monolingual baseline. Analysis of the polyglot models{'} performance provides a new understanding of the similarities and differences between languages in the shared task.",
}
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%0 Conference Proceedings
%T Polyglot Semantic Role Labeling
%A Mulcaire, Phoebe
%A Swayamdipta, Swabha
%A Smith, Noah A.
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F mulcaire-etal-2018-polyglot
%X Previous approaches to multilingual semantic dependency parsing treat languages independently, without exploiting the similarities between semantic structures across languages. We experiment with a new approach where we combine resources from different languages in the CoNLL 2009 shared task to build a single polyglot semantic dependency parser. Notwithstanding the absence of parallel data, and the dissimilarity in annotations between languages, our approach results in improvement in parsing performance on several languages over a monolingual baseline. Analysis of the polyglot models’ performance provides a new understanding of the similarities and differences between languages in the shared task.
%R 10.18653/v1/P18-2106
%U https://aclanthology.org/P18-2106
%U https://doi.org/10.18653/v1/P18-2106
%P 667-672
Markdown (Informal)
[Polyglot Semantic Role Labeling](https://aclanthology.org/P18-2106) (Mulcaire et al., ACL 2018)
ACL
- Phoebe Mulcaire, Swabha Swayamdipta, and Noah A. Smith. 2018. Polyglot Semantic Role Labeling. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 667–672, Melbourne, Australia. Association for Computational Linguistics.