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Call for Participation:
TextGraphs-13 Shared Task on Explanation Regeneration
https://github.com/umanlp/tg2019task
We invite participation in the new shared task on explanation regeneration
associated with the 13th Workshop on Graph-Based Natural Language Processing
(TextGraphs 2019).
All systems participating in the shared task will be invited to submit system description papers.
Each system description paper will be peer-reviewed by (two) other participating teams and will be
presented as a poster at the main workshop.
Overview
========
This shared task focuses on explanation reconstruction, a stepping-stone
towards general multi-hop inference over language. In particular, the inputs
to this task consist of questions and their correct answers. Participating
systems must extract and rank explanation sentences from a provided
structured knowledge base such that the top-ranked sentences provide
a complete explanation for the given answer.
Example
=======
For example, for the question: "Which of the following is an example of an
organism taking in nutrients?" with the correct answer: "a girl eating an
apple", an ideal system would rank the following explanatory statements
at the top of its extracted sentences:
1. A girl means a human girl.
2. Humans are living organisms.
3. Eating is when an organism takes in nutrients in the form of food.
4. Fruits are kinds of foods.
5. An apple is a kind of fruit.
Important Dates
===============
13-05-2019: Example (trial) data release
17-05-2019: Training data release
12-07-2019: Test data release; Evaluation start
26-07-2019: Evaluation end
19-08-2019: System description paper deadline
09-09-2019: Deadline for reviews of system description papers
16-09-2019: Author notifications
30-09-2019: Camera-ready description paper deadline
03-11-2019/04-11-2019: TextGraphs-13 workshop
Data
====
The data used in this shared task contains 1,680 questions drawn from the
AI2 Reasoning Challenge (ARC) dataset (Clark et al., 2018), together with
explanation sentences for their correct answers (Jansen et al., 2018).
The knowledge base supporting these questions contains
approximately 5,000 facts.
Please see the shared task website for more details:
https://github.com/umanlp/tg2019task