@inproceedings{boros-etal-2017-data,
title = "A data-driven approach to verbal multiword expression detection. {PARSEME} Shared Task system description paper",
author = "Boros, Tiberiu and
Pipa, Sonia and
Barbu Mititelu, Verginica and
Tufis, Dan",
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/W17-1716",
doi = "10.18653/v1/W17-1716",
pages = "121--126",
abstract = "{``}Multiword expressions{''} are groups of words acting as a morphologic, syntactic and semantic unit in linguistic analysis. Verbal multiword expressions represent the subgroup of multiword expressions, namely that in which a verb is the syntactic head of the group considered in its canonical (or dictionary) form. All multiword expressions are a great challenge for natural language processing, but the verbal ones are particularly interesting for tasks such as parsing, as the verb is the central element in the syntactic organization of a sentence. In this paper we introduce our data-driven approach to verbal multiword expressions which was objectively validated during the PARSEME shared task on verbal multiword expressions identification. We tested our approach on 12 languages, and we provide detailed information about corpora composition, feature selection process, validation procedure and performance on all languages.",
}
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<abstract>“Multiword expressions” are groups of words acting as a morphologic, syntactic and semantic unit in linguistic analysis. Verbal multiword expressions represent the subgroup of multiword expressions, namely that in which a verb is the syntactic head of the group considered in its canonical (or dictionary) form. All multiword expressions are a great challenge for natural language processing, but the verbal ones are particularly interesting for tasks such as parsing, as the verb is the central element in the syntactic organization of a sentence. In this paper we introduce our data-driven approach to verbal multiword expressions which was objectively validated during the PARSEME shared task on verbal multiword expressions identification. We tested our approach on 12 languages, and we provide detailed information about corpora composition, feature selection process, validation procedure and performance on all languages.</abstract>
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%0 Conference Proceedings
%T A data-driven approach to verbal multiword expression detection. PARSEME Shared Task system description paper
%A Boros, Tiberiu
%A Pipa, Sonia
%A Barbu Mititelu, Verginica
%A Tufis, Dan
%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 boros-etal-2017-data
%X “Multiword expressions” are groups of words acting as a morphologic, syntactic and semantic unit in linguistic analysis. Verbal multiword expressions represent the subgroup of multiword expressions, namely that in which a verb is the syntactic head of the group considered in its canonical (or dictionary) form. All multiword expressions are a great challenge for natural language processing, but the verbal ones are particularly interesting for tasks such as parsing, as the verb is the central element in the syntactic organization of a sentence. In this paper we introduce our data-driven approach to verbal multiword expressions which was objectively validated during the PARSEME shared task on verbal multiword expressions identification. We tested our approach on 12 languages, and we provide detailed information about corpora composition, feature selection process, validation procedure and performance on all languages.
%R 10.18653/v1/W17-1716
%U https://aclanthology.org/W17-1716
%U https://doi.org/10.18653/v1/W17-1716
%P 121-126
Markdown (Informal)
[A data-driven approach to verbal multiword expression detection. PARSEME Shared Task system description paper](https://aclanthology.org/W17-1716) (Boros et al., MWE 2017)
ACL