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Conference Papers Year : 2017

The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions

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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Dates and versions

hal-01504624 , version 1 (10-04-2017)

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  • HAL Id : hal-01504624 , version 1

Cite

Agata Savary, Carlos Ramisch, Silvio Ricardo Cordeiro, Federico Sangati, Veronika Vincze, et al.. The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions. MWE 2017 - Proceedings of the 13th Workshop on Multiword Expressions, Apr 2017, Valencia, Spain. pp.31 - 47. ⟨hal-01504624⟩
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