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First
Call for Papers
19th
Workshop on Multiword Expressions (MWE 2023)
Organized
and sponsored by SIGLEX, the Special Interest Group
on
the Lexicon of the ACL
Full-day
workshop colocated with EACL 2023, Dubrovnik, Croatia, May 2 or 6, 2023
Hybrid
(on-site & on-line)
Submission
deadline: February 13, 2023
MWE
2023 website:
https://multiword.org/mwe2023/
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Multiword expressions (MWEs) are word
combinations
that 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, phrasal verbs, rhetorical figures, collocations, institutionalised phrases, etc. Their behaviour is often unpredictable; for example, their meaning often does not result from the direct combination of
the meanings of their parts. Given their irregular nature, MWEs often pose complex problems in linguistic modelling (e.g. annotation), NLP tasks (e.g. parsing), and end-user applications (e.g. natural language understanding and MT), hence still representing
an open issue for computational linguistics (Constant et al. 2017).
For almost two decades, modelling and processing
MWEs for NLP has been the topic of the MWE workshop organised by the MWE
section of
SIGLEX
in conjunction with major NLP conferences since 2003. Impressive progress has been made in the field, but our understanding of MWEs still requires much research considering their need and usefulness in NLP applications. This is also relevant to domain-specific
NLP pipelines that need to tackle terminologies most often realised as MWEs. Following previous years, for this 19th edition of the workshop, we identified the following topics on which contributions are particularly encouraged:
MWE processing and identification in specialized
languages and domains: Multiword terminology
extraction from domain-specific corpora (Bonin et al. 2010) is of particular importance to various applications, such as MT (Semmar & Laib, 2017), or for the identification and monitoring of neologisms and technical jargon (Chatzitheodorou et al, 2021). We
expect approaches that deal with the processing of MWEs as well as the processing of terminology in specialised domains can benefit from each other.
MWE processing to enhance end-user applications:
MWEs have gained particular attention
in end-user applications, including MT (Zaninello & Birch 2020; Han et al. 2021), simplification (Kochmar et al. 2020), 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). We believe that it is crucial to extend and deepen these first attempts to integrate and evaluate MWE technology in these and further end-user applications.
MWE identification and interpretation in pre-trained
language models: Most current MWE processing
is limited to their identification and detection using pre-trained language models, but we still lack understanding about how MWEs are represented and dealt with therein (Nedumpozhimana & Kelleher 2021; Garcia et al. 2021, Fakharian & Cook 2021), how to better
model the compositionality of MWEs from semantics (Moreau et al. 2018). Now that NLP has shifted towards end-to-end neural models like BERT, capable of solving complex tasks with little or no intermediary linguistic symbols, questions arise about the extent
to which MWEs should be implicitly or explicitly modelled (Shwartz & Dagan, 2019).
MWE processing in low-resource languages:
The PARSEME shared tasks (Ramisch et
al. 2020; 2018; Savary et al. 2017), among others, have fostered significant progress in MWE identification, providing datasets that include low-resource languages, evaluation measures, and tools that now allow fully integrating MWE identification into end-user
applications. A few efforts have recently explored methods for the automatic interpretation of MWEs (Bhatia, et al. 2018; 2017), and their processing in low-resource languages (Liu & Wang 2020; Kumar et al. 2017). Resource creation and sharing should be pursued
in parallel with the development of methods able to capitalize on small datasets (Han et al. 2020).
Through this workshop, we would like to bring
together and encourage researchers in various NLP subfields to submit MWE-related research, so that approaches that deal with processing of MWEs including processing for low-resource languages and for various applications can benefit from each other. We also
intend to consolidate the converging effects of previous joint workshops
LAW-MWE-CxG 2018,
MWE-WN 2019
and
MWE-LEX 2020,
the
joint MWE-WOAH panel in 2021,
and the MWE-SIGUL
2022 joint session, extending our
scope to MWEs in e-lexicons and WordNets, MWE annotation, as well as grammatical constructions. Correspondingly, we call for papers on research related (but not limited) to MWEs and constructions in:
Computationally-applicable theoretical work
in psycholinguistics and corpus linguistics;
Annotation (expert, crowdsourcing, automatic)
and representation in resources such as corpora, treebanks, e-lexicons, and WordNets (also for low-resource languages);
Processing in syntactic and semantic frameworks
(e.g. CCG, CxG, HPSG, LFG, TAG, UD, etc.);
Discovery and identification methods, including
for specialized languages and domains such as clinical or biomedical NLP;
Interpretation of MWEs and understanding of
text containing them;
Language acquisition, language learning, and
non-standard language (e.g. tweets, speech);
Evaluation of annotation and processing techniques;
Retrospective comparative analyses from the
PARSEME shared tasks;
Processing for end-user applications (e.g. MT,
NLU, summarisation, language learning, etc.);
Implicit and explicit representation in pre-trained
language models and end-user applications;
Evaluation and probing of pre-trained language
models;
Resources and tools (e.g. lexicons, identifiers)
and their integration into end-user applications;
Multiword terminology extraction;
Adaptation and transfer of annotations and related
resources to new languages and domains including low-resource ones.
Shared Task
We do not have a shared task this year, but
a new release of the PARSEME corpus of verbal MWEs is currently underway. We encourage submission of research papers that include analyses of the new edition of the PARSEME data and improvements over the results for PARSEME 2020 shared task as well as SemEval
2022 task 2 on idiomaticity prediction.
Submission formats:
The workshop invites two types of submissions:
archival submissions
that present substantially original research in both long
paper format (8 pages + references)
and short paper
format (4 pages + references).
non-archival submissions
of abstracts describing relevant research presented/published elsewhere which will not be included in the MWE proceedings.
Paper submission and templates
Papers should be submitted via the workshop’s
START submission page, available soon. Please choose the appropriate submission format (archival/non-archival). Archival papers with existing reviews will also be accepted through the ACL Rolling Review. Submissions must follow the
ACL
2023 stylesheet.
Important Dates
Paper Submission Deadline:
February
13, 2023
Notification of acceptance:
March
13, 2023
Camera-ready papers due:
March
27, 2023
Workshop:
May
2 or 6, 2023
All deadlines are at 23:59 UTC-12 (Anywhere
on Earth).
Organizing Committee
Program
chairs: Marcos Garcia, Voula Giouli, Lifeng Han, Shiva Taslimipoor
Publication
chair: Archna Bhatia
Publicity
chair: Kilian Evang
Anti-harassment
policy
The
workshop follows the ACL
anti-harrassment policy.
Contact
For any inquiries regarding the workshop, please
send an email to the Organizing Committee at mwe2023@googlegroups.com.