MWE 2021: 17th Workshop on Multiword Expressions - first CfP

[apologies for cross-postings]


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17th Workshop on Multiword Expressions (MWE 2021)

Colocated with ACL-IJCNLP 2021 (Bangkok, Thailand), 5 or 6 August 2021


***Deadline: April 19, 2021***


https://multiword.org/mwe2021/


Second call for papers

Organised and sponsored by: SIGLEX, the Special Interest Group on the

Lexicon of the ACL

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Multiword expressions (MWEs) are word combinations which exhibit

lexical, syntactic, semantic, pragmatic and/or statistical

idiosyncrasies (Baldwin & Kim 2010), such as by and large, hot dog,

pay a visit and pull one's leg. The notion encompasses closely related

phenomena: idioms, compounds, light-verb constructions, rhetorical

figures, institutionalised phrases, collocations, etc. The behaviour

of MWEs is often unpredictable, in particular their meanings are not

regularly composed of the meanings of their parts. Thus, MWEs are a

major challenge in computational linguistics (Constant et al. 2017),

including linguistic modelling (e.g. treebanking), computational

modelling (e.g. parsing), and end-user NLP applications (e.g. natural

language understanding, machine translation, and social media mining).


Modelling and processing MWEs for NLP has been the topic of the MWE

workshop organised by the MWE section (see https://multiword.org) of

SIGLEX in conjunction with major NLP conferences since 2003. Although

much progress has been made in the field, MWE processing in end-user

NLP tasks is currently under-explored, and most studies still

introduce MWEs as future work. Nonetheless, there are recent studies

in which MWEs gained particular attention in end-user applications,

including machine translation (Zaninello & Birch 2020), text

simplification (Kochmar et al. 2020, Liu & Hwa 2016), language

learning and assessment (Paquot et al. 2019, Christiansen & Arnon

2017), social media mining (Maisto et al. 2017), and abusive language

detection (Zampieri et al. 2020, Caselli et al. 2020).


The special focus for this 17th edition of the workshop is on MWE

processing in end-user applications such as those listed above. On the

one hand, the PARSEME shared tasks (Ramisch et al. 2020, Ramisch et

al. 2018, Savary et al. 2017), among others, fostered significant

progress in MWE identification, providing datasets, evaluation

measures and tools that now allow fully integrating MWE identification

into end-user applications. On the other hand, NLP seems to be

shifting towards end-to-end neural models capable of solving complex

end-user tasks with little or no intermediary linguistic symbols,

questioning the extent to which MWEs should be implicitly or

explicitly modelled. Therefore, one goal of this workshop is to bring

together and encourage researchers in various NLP subfields to submit

MWE-related research, so that approaches that deal with MWEs in

various applications could benefit from each other.


Following the success of previous joint workshops LAW-MWE-CxG 2018,

MWE-WN 2019 and MWE-LEX 2020, we further extend the scope of the

workshop to MWEs in e-lexicons and WordNets, MWE annotation, as well

as grammatical constructions.


The 17th Workshop on MWEs invites submissions on (but not limited to)

the following topics:


**Traditional MWE topics:**


- Computationally-applicable theoretical work on MWEs and

constructions in psycholinguistics and corpus linguistics

- MWE and construction annotation and representation in resources such

as corpora, treebanks, e-lexicons and WordNets

- Processing of MWEs and constructions in syntactic and semantic

frameworks (e.g. CCG, CxG, HPSG, LFG, TAG, UD, etc.)

- Discovery and identification methods for MWEs and constructions

- MWEs and constructions in language acquisition, language learning,

and non-standard language (e.g. tweets, speech)

- Evaluation of annotation and processing techniques for MWEs and constructions

- Retrospective comparative analyses from the PARSEME shared tasks on

automatic identification of MWEs


**Topics on MWEs and end-user applications:**


- Processing of MWEs and constructions in end-user applications (e.g.

MT, NLU, summarisation, social media mining, computer assisted

language learning)

- Implicit and explicit representation of MWEs and constructions in

end-user applications

- Evaluation of end-user applications concerning MWEs and constructions

- Resources and tools for MWEs and constructions (e.g. lexicons,

identifiers) in end-user applications


== JOINT SESSION WITH WOAH WORKSHOP ==


Pursuing the MWE Section's tradition of synergies with other

communities and in accordance with ACL-IJCNLP 2021's theme track on

NLP for social good, we will organise a joint session with the

Workshop on Online Abuse and Harm (WOAH) (see

https://www.workshopononlineabuse.com/) . We believe that MWEs are

important in online abuse detection, and that the latter can provide

an interesting testbed for MWE processing technology. The main goal is

to pave the way towards the creation of data for a shared task

involving both communities. The format of the session is under

discussion, and we welcome suggestions from the community. Submissions

describing research on MWEs and abusive language, especially

introducing new datasets, are also welcome.


== SUBMISSION MODALITIES ==


- Long papers (8 content pages + references) should report on solid

and finished research including new experimental results, resources

and/or techniques.


- Short papers (4 content pages + references) should report on small

experiments, focused contributions, ongoing research, negative results

and/or philosophical discussion.


In regular research papers, the reported research should be

substantially original. Papers available as preprints can also be

submitted provided that they fulfil the conditions defined by the ACL

Policies for Submission, Review and Citation (see

https://www.aclweb.org/portal/content/new-policies-submission-review-and-citation),

in particular the ACL Author Guidelines (see

https://www.aclweb.org/adminwiki/index.php?title=ACL_Author_Guidelines).

Notice that double submission to ACL-IJCNLP 2021 main conference and

MWE 2021 is allowed but should be notified at submission time, as per

the ACL-IJCNLP 2021 call for papers (see

https://2021.aclweb.org/calls/papers/#multiple-submission-policy):

"[...] papers can be dual-submitted to both ACL-IJCNLP 2021 and an

ACL-IJCNLP 2021 workshop which has its submission deadline falling

before our notification date of May 5, 2021."


Submission is double-blind as per the ACL-IJCNLP 2021 guidelines (see

https://2021.aclweb.org/calls/papers/#paper-submission-information).

For all types of submission, the ACL-IJCNLP 2021 templates (see

https://2021.aclweb.org/calls/papers/#paper-submission-and-templates)

must be used. There is no limit on the number of reference pages. An

extra page will be allowed to take the reviewers' comments into

account in the final versions of accepted papers (long = 9 content

pages, short = 5 content pages).


The decisions as to oral or poster presentations of the selected

papers will be taken by the PC chairs, depending on the available

infrastructure for participation (presential and/or virtual). No

distinction between papers presented orally and as posters is made in

the workshop proceedings.


All papers should be submitted via the workshop's START space,

available soon. Please choose the appropriate submission modality

(long/short):

https://www.softconf.com/acl2021/w14_MWE2021/.



== CONTACT ==


For any inquiries regarding the workshop please send an email to

mweworkshop2021@gmail.com<mailto:mweworkshop2021@gmail.com>


== IMPORTANT DATES ==


All deadlines are at 23:59 UTC-12 (anywhere in the world).


- April 19, 2021: Paper Submission Deadline

- May 28, 2021: Notification of Acceptance

- June 7, 2021: Camera-ready papers due

- August 5 or 6, 2021: Workshop (Date TBD)


== ORGANIZERS ==


Program chairs: Paul Cook, Jelena Mitrović, Carla Parra Escartín and

Ashwini Vaidya

Publication chairs: Petya Osenova and Shiva Taslimipoor

Communication chair: Carlos Ramisch