ACL 2020 Workshop on Figurative Language Processing
Seattle, WA, USA – July 9 or 10, 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: https://www.softconf.com/acl2020/flp/ <https://www.google.com/url?q=https%3A%2F%2Fwww.softconf.com%2Facl2020%2Fflp%2F&sa=D&sntz=1&usg=AFQjCNFCh0dmvhrW7eEpCPoI_OeYZQ3KQQ>
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 or 10, 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 CodaLab website: https://competitions.codalab.org/competitions/22188.
*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: https://competitions.codalab.org/competitions/22247.
Beata Beigman Klebanov, Educational Testing Service, USA
Ekaterina Shutova, University of Cambridge, UK
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 -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 4835 bytes Desc: not available URL: <https://mailman.uib.no/public/corpora/attachments/20200219/3acd3677/attachment.txt>