30.4884, FYI: Call for Participation: SemEval-2020 Shared Task 5

[The LINGUIST List]

LINGUIST List: Vol-30-4884. Sat Dec 28 2019. ISSN: 1069 - 4875.

Subject: 30.4884, FYI: Call for Participation: SemEval-2020 Shared Task 5

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Date: Sat, 28 Dec 2019 18:43:51
From: Xiaoyu Yang [xiaoyu.yang94 at hotmail.com]
Subject: Call for Participation: SemEval-2020 Shared Task 5

 
Second call for participants:

SemEval 2020 Task 5: Modelling Causal Reasoning in Language: Detecting
Counterfactuals

Please find more details on the Task-5 Codalab webpage, participants could
submit and evaluate the results on Codalab:
https://competitions.codalab.org/competitions/21691

**The new eval date of our task is Februray 19th, 2020.  We have released the
training data, and will release the test data when the evaluation starts.**

[ Task Description ]

To model counterfactual semantics and reasoning in natural language, our
shared task aims to provide a benchmark for two basic problems.

Subtask1: Detecting counterfactual statements:

In this task, you are asked to determine whether a given statement is
counterfactual or not. Counterfactual statements describe events that did not
actually happen or cannot happen, as well as the possible consequence if the
events have had happened. More specifically, counterfactuals describe events
counter to facts and hence naturally involve common sense, knowledge, and
reasoning. Tackling this problem is the basis for all down-stream
counterfactual related causal inference analysis in natural language. For
example, the following statements are counterfactuals that need to be
detected: Her post-traumatic stress could have been avoided if a combination
of paroxetine and exposure therapy had been prescribed two months earlier.

Subtask2: Detecting antecedent and consequence:

Indicating causal insight is an inherent characteristic of counterfactual. To
further detect the causal knowledge conveyed in counterfactual statements,
subtask 2 aims to locate antecedent and consequent in counterfactuals.
Consider the “post-traumatic stress” example discussed above, the antecedent
part is 'if a combination of paroxetine and exposure therapy had been
prescribed two months earlier', and the consequent part is 'Her post-traumatic
stress could have been avoided'. Such causal relations indicated by
counterfactuals can be not only used for analyzing the specific statement but
also be accumulated across corpora to develop domain causal knowledge.
 

[ Important Dates ]
Official website: http://alt.qcri.org/semeval2020/
19 February 2020: Evaluation start (will release the test set then)**
11 March 2020: Evaluation end**
18 March 2020: Results posted
17 April 2020: System description paper submissions due
24 April 2020: Task description paper submissions due
10 Jun 2020: Author notifications
1 Jul 2020: Camera ready submissions due
13-14 September 2020:  SemEval 2020

[ Task Organizers ]
Xiaodan Zhu, Queen's University
Xiaoyu Yang, Queen's University
Huasha Zhao, Alibaba Group
Qiong Zhang, Alibaba Group
Stan Matwin, Dalhousie University
 



Linguistic Field(s): Applied Linguistics
                     Computational Linguistics
                     General Linguistics





 



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