@inproceedings{savary-etal-2017-parseme,
title = "The {PARSEME} Shared Task on Automatic Identification of Verbal Multiword Expressions",
author = "Savary, Agata and
Ramisch, Carlos and
Cordeiro, Silvio and
Sangati, Federico and
Vincze, Veronika and
QasemiZadeh, Behrang and
Candito, Marie and
Cap, Fabienne and
Giouli, Voula and
Stoyanova, Ivelina and
Doucet, Antoine",
editor = "Markantonatou, Stella and
Ramisch, Carlos and
Savary, Agata and
Vincze, Veronika",
booktitle = "Proceedings of the 13th Workshop on Multiword Expressions ({MWE} 2017)",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-1704",
doi = "10.18653/v1/W17-1704",
pages = "31--47",
abstract = "Multiword expressions (MWEs) are known as a {``}pain in the neck{''} for NLP due to their idiosyncratic behaviour. While some categories of MWEs have been addressed by many studies, verbal MWEs (VMWEs), such as to take a decision, to break one{'}s heart or to turn off, have been rarely modelled. This is notably due to their syntactic variability, which hinders treating them as {``}words with spaces{''}. We describe an initiative meant to bring about substantial progress in understanding, modelling and processing VMWEs. It is a joint effort, carried out within a European research network, to elaborate universal terminologies and annotation guidelines for 18 languages. Its main outcome is a multilingual 5-million-word annotated corpus which underlies a shared task on automatic identification of VMWEs. This paper presents the corpus annotation methodology and outcome, the shared task organisation and the results of the participating systems.",
}
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%0 Conference Proceedings
%T The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions
%A Savary, Agata
%A Ramisch, Carlos
%A Cordeiro, Silvio
%A Sangati, Federico
%A Vincze, Veronika
%A QasemiZadeh, Behrang
%A Candito, Marie
%A Cap, Fabienne
%A Giouli, Voula
%A Stoyanova, Ivelina
%A Doucet, Antoine
%Y Markantonatou, Stella
%Y Ramisch, Carlos
%Y Savary, Agata
%Y Vincze, Veronika
%S Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F savary-etal-2017-parseme
%X Multiword expressions (MWEs) are known as a “pain in the neck” for NLP due to their idiosyncratic behaviour. While some categories of MWEs have been addressed by many studies, verbal MWEs (VMWEs), such as to take a decision, to break one’s heart or to turn off, have been rarely modelled. This is notably due to their syntactic variability, which hinders treating them as “words with spaces”. We describe an initiative meant to bring about substantial progress in understanding, modelling and processing VMWEs. It is a joint effort, carried out within a European research network, to elaborate universal terminologies and annotation guidelines for 18 languages. Its main outcome is a multilingual 5-million-word annotated corpus which underlies a shared task on automatic identification of VMWEs. This paper presents the corpus annotation methodology and outcome, the shared task organisation and the results of the participating systems.
%R 10.18653/v1/W17-1704
%U https://aclanthology.org/W17-1704
%U https://doi.org/10.18653/v1/W17-1704
%P 31-47
Markdown (Informal)
[The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions](https://aclanthology.org/W17-1704) (Savary et al., MWE 2017)
ACL
- Agata Savary, Carlos Ramisch, Silvio Cordeiro, Federico Sangati, Veronika Vincze, Behrang QasemiZadeh, Marie Candito, Fabienne Cap, Voula Giouli, Ivelina Stoyanova, and Antoine Doucet. 2017. The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions. In Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017), pages 31–47, Valencia, Spain. Association for Computational Linguistics.