@inproceedings{ramisch-etal-2020-edition,
title = "Edition 1.2 of the {PARSEME} Shared Task on Semi-supervised Identification of Verbal Multiword Expressions",
author = {Ramisch, Carlos and
Savary, Agata and
Guillaume, Bruno and
Waszczuk, Jakub and
Candito, Marie and
Vaidya, Ashwini and
Barbu Mititelu, Verginica and
Bhatia, Archna and
I{\~n}urrieta, Uxoa and
Giouli, Voula and
G{\"u}ng{\"o}r, Tunga and
Jiang, Menghan and
Lichte, Timm and
Liebeskind, Chaya and
Monti, Johanna and
Ramisch, Renata and
Stymne, Sara and
Walsh, Abigail and
Xu, Hongzhi},
editor = "Markantonatou, Stella and
McCrae, John and
Mitrovi{\'c}, Jelena and
Tiberius, Carole and
Ramisch, Carlos and
Vaidya, Ashwini and
Osenova, Petya and
Savary, Agata",
booktitle = "Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons",
month = dec,
year = "2020",
address = "online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.mwe-1.14",
pages = "107--118",
abstract = "We present edition 1.2 of the PARSEME shared task on identification of verbal multiword expressions (VMWEs). Lessons learned from previous editions indicate that VMWEs have low ambiguity, and that the major challenge lies in identifying test instances never seen in the training data. Therefore, this edition focuses on unseen VMWEs. We have split annotated corpora so that the test corpora contain around 300 unseen VMWEs, and we provide non-annotated raw corpora to be used by complementary discovery methods. We released annotated and raw corpora in 14 languages, and this semi-supervised challenge attracted 7 teams who submitted 9 system results. This paper describes the effort of corpus creation, the task design, and the results obtained by the participating systems, especially their performance on unseen expressions.",
}
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<abstract>We present edition 1.2 of the PARSEME shared task on identification of verbal multiword expressions (VMWEs). Lessons learned from previous editions indicate that VMWEs have low ambiguity, and that the major challenge lies in identifying test instances never seen in the training data. Therefore, this edition focuses on unseen VMWEs. We have split annotated corpora so that the test corpora contain around 300 unseen VMWEs, and we provide non-annotated raw corpora to be used by complementary discovery methods. We released annotated and raw corpora in 14 languages, and this semi-supervised challenge attracted 7 teams who submitted 9 system results. This paper describes the effort of corpus creation, the task design, and the results obtained by the participating systems, especially their performance on unseen expressions.</abstract>
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%0 Conference Proceedings
%T Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions
%A Ramisch, Carlos
%A Savary, Agata
%A Guillaume, Bruno
%A Waszczuk, Jakub
%A Candito, Marie
%A Vaidya, Ashwini
%A Barbu Mititelu, Verginica
%A Bhatia, Archna
%A Iñurrieta, Uxoa
%A Giouli, Voula
%A Güngör, Tunga
%A Jiang, Menghan
%A Lichte, Timm
%A Liebeskind, Chaya
%A Monti, Johanna
%A Ramisch, Renata
%A Stymne, Sara
%A Walsh, Abigail
%A Xu, Hongzhi
%Y Markantonatou, Stella
%Y McCrae, John
%Y Mitrović, Jelena
%Y Tiberius, Carole
%Y Ramisch, Carlos
%Y Vaidya, Ashwini
%Y Osenova, Petya
%Y Savary, Agata
%S Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons
%D 2020
%8 December
%I Association for Computational Linguistics
%C online
%F ramisch-etal-2020-edition
%X We present edition 1.2 of the PARSEME shared task on identification of verbal multiword expressions (VMWEs). Lessons learned from previous editions indicate that VMWEs have low ambiguity, and that the major challenge lies in identifying test instances never seen in the training data. Therefore, this edition focuses on unseen VMWEs. We have split annotated corpora so that the test corpora contain around 300 unseen VMWEs, and we provide non-annotated raw corpora to be used by complementary discovery methods. We released annotated and raw corpora in 14 languages, and this semi-supervised challenge attracted 7 teams who submitted 9 system results. This paper describes the effort of corpus creation, the task design, and the results obtained by the participating systems, especially their performance on unseen expressions.
%U https://aclanthology.org/2020.mwe-1.14
%P 107-118
Markdown (Informal)
[Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions](https://aclanthology.org/2020.mwe-1.14) (Ramisch et al., MWE 2020)
ACL
- Carlos Ramisch, Agata Savary, Bruno Guillaume, Jakub Waszczuk, Marie Candito, Ashwini Vaidya, Verginica Barbu Mititelu, Archna Bhatia, Uxoa Iñurrieta, Voula Giouli, Tunga Güngör, Menghan Jiang, Timm Lichte, Chaya Liebeskind, Johanna Monti, Renata Ramisch, Sara Stymne, Abigail Walsh, and Hongzhi Xu. 2020. Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions. In Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons, pages 107–118, online. Association for Computational Linguistics.