SeMantic Answer Type and Relation Prediction Task (SMART 2021)
ISWC 2021 Semantic Web Challenge
in conjunction with ISWC 2021 [https://iswc2021.semanticweb.org/]
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Challenge website: https://smart-task.github.io/2021/
Conference date and location: 24 – 28 October 2021 (Online – Virtual)
Submission deadline: September 15, 2021
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Brief Background
Knowledge Base Question Answering (KBQA) is a popular task in the field of Natural Language Processing and Information Retrieval, in which the goal is to answer a natural language question using the facts in a Knowledge Base. KBQA can involve several subtasks such as entity linking, relation linking, and answer type prediction. In SMART 2021 Semantic Web Challenge, we focus on two subtasks in KBQA.
Task Descriptions
This year, in the second iteration of the SMART challenge, we have two independent tasks:
Task 1 – Answer Type Prediction: Given a question in natural language, the task is to predict the type of the answer using a set of candidates from a target ontology.
– Who is the heaviest player of the Chicago Bulls? -) dbo:BasketballPlayer
– How many employees does IBM have? -) number
Task 2 – Relation prediction: Given a question in natural language, the task is to predict the relations needed to extract the correct answer from the KB.
– Who are the actors starring in movies directed by and starring William Shatner? -) dbo:starring, dbo:director
– What games can be played in schools founded by Fr. Orlando? -) dbo:sport, dbo:foundedBy
Datasets
We have created datasets for each task; SMART2021-AT and SMART2021-RL. Each of these tasks has separate datasets for DBpedia and Wikidata. More details are available on the challenge website.
Submissions and proceedings
Training data for the tasks are available now and the test data will be provided to the participants by the 31st of August. Participants are required to send their system outputs by the 15th of September. Participants are invited to submit a system paper that will be peer-reviewed and published in a CEUR volume similar to last year, http://ceur-ws.org/Vol-2774/.
Please feel free to contact the organizers regarding any inquiries related to the task, datasets, and submissions. There is a slack workspace for challenge related discussions.
Organizers
Nandana Mihindukulasooriya, IBM Research AI, USA
Mohnish Dubey, University of Bonn, Germany
Alfio Gliozzo, IBM Research AI, USA
Jens Lehmann, University of Bonn, Germany
Axel-Cyrille Ngonga Ngomo, Paderborn University, Germany
Ricardo Usbeck, University of Hamburg, Germany
Gaetano Rossiello, IBM Research AI, USA
Uttam Kumar, University of Bonn, Germany