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FigLang 2020 : ACL 2020 Workshop on Figurative Language Processing


When Jul 9, 2020 - Jul 9, 2020
Where Seattle, WA, USA
Submission Deadline Apr 18, 2020
Notification Due May 8, 2020
Final Version Due May 18, 2020
Categories    NLP

Call For Papers


ACL 2020 Workshop on Figurative Language Processing

Seattle, WA, USA – July 9, 2020

Submission deadline: April 18, 2020


Figurative language processing is a rapidly growing area in NLP,
including processing of metaphors, idioms, puns, irony, sarcasm, as
well as other figures. Characteristic to all areas of human activity (from
poetic to ordinary to scientific) and, thus, to all types of discourse,
figurative language becomes an important problem for NLP systems. Its
ubiquity in language has been established in a number of corpus
studies and the role it plays in human reasoning has been confirmed in
psychological experiments. This makes figurative language an
important research area for computational and cognitive linguistics,
and its automatic identification and interpretation indispensable for any
semantics-oriented NLP application.

The main focus of the workshop will be on computational modelling of
figurative language using state-of-the-art NLP techniques. However,
papers on cognitive, linguistic, social, rhetorical, and applied aspects
are also of interest, provided that they are presented within a
computational, a formal, or a quantitative framework. In addition, we
will also conduct two shared tasks on metaphor and sarcasm detection.

The workshop invites both full papers and short papers for either oral
or poster presentation.
Submission site:


April 18, 2020 Paper submissions due (23:59 West Coast USA time)

May 8, 2020 Notification of acceptance

May 18, 2020 Camera-ready papers due

June 9, 2020 Workshop in Seattle, Washington


*Metaphor detection shared task*

Following a successful shared task on metaphor detection in news,
editorial, conversations, and academic writing sampled from the BNC
during the Workshop on Figurative Language Processing in 2018, we
will expand to a new domain and conduct a shared task on detection of
metaphors in persuasive essays written by non-native speakers of
English. Beigman Klebanov, Leong, and Flor (NAACL 2018) showed that
usage of metaphorical language that is related to the writer’s
arguments is correlated with the human holistic scores of essay quality.
We will use the annotated dataset from the Beigman Klebanov et al
(2018) study to conduct the shared task, and use their results as a
baseline. We also intend to publish the features to help participants
directly build on the prior work. In addition, we will run a second round
of competition on the BNC data, to help track improvements on this
benchmark since the last shared task.

For more information about the shared task and to participate visit our

*Sarcasm detection shared task*

The second shared task will be on sarcasm detection. Sarcasm
detection has received considerable attention in the NLP community in
recent years (Joshi, 2016). This current shared task aims to study the
role of conversation context for sarcasm detection (Ghosh et al., 2018).
We will be using two different datasets: Twitter conversations and
conversation threads from Reddit. For both datasets, we will provide
the immediate context (i.e., only the previous dialogue turn) as well as
the full dialogue thread, when available. The goal is to understand how
much conversation context is needed or helpful for sarcasm detection.

For more information about the shared task and to participate visit our
CodaLab site:


Beata Beigman Klebanov, Educational Testing Service, USA

Ekaterina Shutova, University of Amsterdam, The Netherlands

Smaranda Muresan, Columbia University, USA

Patricia Lichtenstein, University of California, Merced, USA

Ben Leong, Educational Testing Service, USA

Anna Feldman, Montclair State University, USA

Debanjan Ghosh, Educational Testing Service, USA

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