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-millionword 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.

The ATILF-LLF System for Parseme Shared Task: a Transition-based Verbal Multiword Expression Tagger

“…Each transition is (CS, MT, RO, SL), and for the third group (the 10 remaining languages) full dependency parses are provided. See (Savary et al, 2017) for more information on the data sets. [1,2,3,4,5,6] The transitions of this system are limited to the following: (a) the Shift transition takes the first element in the buffer and pushes it onto the stack; (b) the Merge transition removes the two top elements of the stack, combines them as a single element, and adds it to the stack; 3 (c) the Complete transition moves the upper element of the stack to L, whether the element is a single token or an identified VMWE and finally (d) the Complete-MWT transition, only valid for multiword tokens 3 The newly created element is assigned linguistic attributes using basic concatenation rules that would deserve to be improved in future experiments: e.g., the lemma is the concatenation of the lemmas of the two initial elements.…”

Microsyntactic Annotation of Corpora and its Use in Computational Linguistics Tasks

“…a recent overview [20], with extensive bibliography, and a comprehensive paper [21] on corpus annotation with verbal MWEs -specifically, light verb constructions of various types). It may seem, at first glance, that our research exactly falls within MWE annotation framework.…”

Boundary-based MWE segmentation with text partitioning

“…To evaluate against a diversity of languages this work also utilizes data produced by the multinational, European Cooperation in Science and Technology's action group: PARSing and Multiword Expressions within a European multilingual network (PARSEME) (Savary et al, 2015). In 2017, the PARSEME group conducted a shared task with data spanning 18 languages 3 (Savary et al, 2017), focusing on several classes of verbal MWEs. So, while the PARSEME data are not annotated for all MWEs classes, they do provide an assessment against multiple languages.…”