Proceedings of the SeMantic Answer Type and Relation Prediction Task at ISWC 2021 Semantic Web Challenge (SMART2021)
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CEUR-WS.org, 2022. 88 S. (CEUR Workshop Proceedings; Band 3119).
Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung
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TY - BOOK
T1 - Proceedings of the SeMantic Answer Type and Relation Prediction Task at ISWC 2021 Semantic Web Challenge (SMART2021)
A2 - Mihindukulasooriya, Nandana
A2 - Dubey, Mohnish
A2 - Gliozzo, Alfio
A2 - Lehmann, Jens
A2 - Ngomo, Axel-Cyrille Ngonga
A2 - Usbeck, Ricardo
A2 - Rossiello, Gaetano
A2 - Kumar, Uttam
PY - 2022/10
Y1 - 2022/10
N2 - Each year the International Semantic Web Conference organizes a set of Semantic Web Challenges to establish competitions that will advance state-of-the-art solutions in some problem domains. The Semantic Answer Type and Relation Prediction Task (SMART) task is one of the ISWC 2021 Semantic Web challenges. This is the second year of the challenge after a successful SMART 2020 at ISWC 2020. This year's version focuses on two sub-tasks that are very important to Knowledge Base Question Answering (KBQA): Answer Type Prediction and Relation Prediction. Question type and answer type prediction can play a key role in knowledge base question answering systems providing insights about the expected answer that are helpful to generate correct queries or rank the answer candidates. More concretely, given a question in natural language, the first task is, to predict the answer type using a target ontology (e.g., DBpedia or Wikidata. Similarly, the second task is to identify relations in the natural language query and link them to the relations in a target ontology. This paper discusses the task descriptions, benchmark datasets, and evaluation metrics. For more information, please visit https://smart-task.github.io/2021/.
AB - Each year the International Semantic Web Conference organizes a set of Semantic Web Challenges to establish competitions that will advance state-of-the-art solutions in some problem domains. The Semantic Answer Type and Relation Prediction Task (SMART) task is one of the ISWC 2021 Semantic Web challenges. This is the second year of the challenge after a successful SMART 2020 at ISWC 2020. This year's version focuses on two sub-tasks that are very important to Knowledge Base Question Answering (KBQA): Answer Type Prediction and Relation Prediction. Question type and answer type prediction can play a key role in knowledge base question answering systems providing insights about the expected answer that are helpful to generate correct queries or rank the answer candidates. More concretely, given a question in natural language, the first task is, to predict the answer type using a target ontology (e.g., DBpedia or Wikidata. Similarly, the second task is to identify relations in the natural language query and link them to the relations in a target ontology. This paper discusses the task descriptions, benchmark datasets, and evaluation metrics. For more information, please visit https://smart-task.github.io/2021/.
KW - Informatics
U2 - 10.48550/arXiv.2112.07606
DO - 10.48550/arXiv.2112.07606
M3 - Conference proceedings
VL - 3119
T3 - CEUR Workshop Proceedings
BT - Proceedings of the SeMantic Answer Type and Relation Prediction Task at ISWC 2021 Semantic Web Challenge (SMART2021)
PB - CEUR-WS.org
ER -