Each year the International Semantic Web Conference accepts a set of Semantic Web Challenges to establish competitions that will advance the state of the art solutions in any given problem domain. The SeMantic AnsweR Type prediction task (SMART) was part of ISWC 2020 challenges. Question type and answer type prediction can play a key role in knowledge base question answering systems providing insights that are helpful to generate correct queries or rank the answer candidates. More concretely, given a question in natural language, the task of SMART challenge is, to predict the answer type using a target ontology (e.g., DBpedia or Wikidata).
%0 Journal Article
%1 Mihindukulasooriya2020-dy
%A Mihindukulasooriya, Nandana
%A Dubey, Mohnish
%A Gliozzo, Alfio
%A Lehmann, Jens
%A Ngomo, Axel-Cyrille Ngonga
%A Usbeck, Ricardo
%D 2020
%I arXiv
%K
%T SeMantic AnsweR Type prediction task (SMART) at ISWC 2020 Semantic Web Challenge
%X Each year the International Semantic Web Conference accepts a set of Semantic Web Challenges to establish competitions that will advance the state of the art solutions in any given problem domain. The SeMantic AnsweR Type prediction task (SMART) was part of ISWC 2020 challenges. Question type and answer type prediction can play a key role in knowledge base question answering systems providing insights that are helpful to generate correct queries or rank the answer candidates. More concretely, given a question in natural language, the task of SMART challenge is, to predict the answer type using a target ontology (e.g., DBpedia or Wikidata).
@article{Mihindukulasooriya2020-dy,
abstract = {Each year the International Semantic Web Conference accepts a set of Semantic Web Challenges to establish competitions that will advance the state of the art solutions in any given problem domain. The SeMantic AnsweR Type prediction task (SMART) was part of ISWC 2020 challenges. Question type and answer type prediction can play a key role in knowledge base question answering systems providing insights that are helpful to generate correct queries or rank the answer candidates. More concretely, given a question in natural language, the task of SMART challenge is, to predict the answer type using a target ontology (e.g., DBpedia or Wikidata).},
added-at = {2024-09-10T11:56:37.000+0200},
author = {Mihindukulasooriya, Nandana and Dubey, Mohnish and Gliozzo, Alfio and Lehmann, Jens and Ngomo, Axel-Cyrille Ngonga and Usbeck, Ricardo},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/205302b0669af3fc644885cef4d607e85/scadsfct},
interhash = {ad1f01b5f362f52f050b69a1551ec7c5},
intrahash = {05302b0669af3fc644885cef4d607e85},
keywords = {},
publisher = {arXiv},
timestamp = {2024-09-10T15:15:57.000+0200},
title = {{SeMantic} {AnsweR} Type prediction task ({SMART}) at {ISWC} 2020 Semantic Web Challenge},
year = 2020
}
