@inproceedings{zampieri-etal-2018-veyn,
title = "{V}eyn at {PARSEME} Shared Task 2018: Recurrent Neural Networks for {VMWE} Identification",
author = "Zampieri, Nicolas and
Scholivet, Manon and
Ramisch, Carlos and
Favre, Benoit",
editor = "Savary, Agata and
Ramisch, Carlos and
Hwang, Jena D. and
Schneider, Nathan and
Andresen, Melanie and
Pradhan, Sameer and
Petruck, Miriam R. L.",
booktitle = "Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions ({LAW}-{MWE}-{C}x{G}-2018)",
month = aug,
year = "2018",
address = "Santa Fe, New Mexico, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-4933",
pages = "290--296",
abstract = "This paper describes the Veyn system, submitted to the closed track of the PARSEME Shared Task 2018 on automatic identification of verbal multiword expressions (VMWEs). Veyn is based on a sequence tagger using recurrent neural networks. We represent VMWEs using a variant of the begin-inside-outside encoding scheme combined with the VMWE category tag. In addition to the system description, we present development experiments to determine the best tagging scheme. Veyn is freely available, covers 19 languages, and was ranked ninth (MWE-based) and eight (Token-based) among 13 submissions, considering macro-averaged F1 across languages.",
}
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%0 Conference Proceedings
%T Veyn at PARSEME Shared Task 2018: Recurrent Neural Networks for VMWE Identification
%A Zampieri, Nicolas
%A Scholivet, Manon
%A Ramisch, Carlos
%A Favre, Benoit
%Y Savary, Agata
%Y Ramisch, Carlos
%Y Hwang, Jena D.
%Y Schneider, Nathan
%Y Andresen, Melanie
%Y Pradhan, Sameer
%Y Petruck, Miriam R. L.
%S Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018)
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F zampieri-etal-2018-veyn
%X This paper describes the Veyn system, submitted to the closed track of the PARSEME Shared Task 2018 on automatic identification of verbal multiword expressions (VMWEs). Veyn is based on a sequence tagger using recurrent neural networks. We represent VMWEs using a variant of the begin-inside-outside encoding scheme combined with the VMWE category tag. In addition to the system description, we present development experiments to determine the best tagging scheme. Veyn is freely available, covers 19 languages, and was ranked ninth (MWE-based) and eight (Token-based) among 13 submissions, considering macro-averaged F1 across languages.
%U https://aclanthology.org/W18-4933
%P 290-296
Markdown (Informal)
[Veyn at PARSEME Shared Task 2018: Recurrent Neural Networks for VMWE Identification](https://aclanthology.org/W18-4933) (Zampieri et al., LAW-MWE 2018)
ACL