论文标题
语义答案类型预测任务（SMART）在ISWC 2020语义Web挑战
SeMantic AnsweR Type prediction task (SMART) at ISWC 2020 Semantic Web Challenge
论文作者
论文摘要
每年，国际语义网络会议都会接受一系列语义网络挑战，以建立竞争，这些竞争将在任何给定的问题领域中推进最先进的解决方案。语义答案类型预测任务（SMART）是ISWC 2020挑战的一部分。问题类型和答案类型预测可以在知识基础问题答案系统中起关键作用，从而提供有助于生成正确查询或对答案候选者进行排名的见解。更具体地说，考虑到自然语言的问题，智能挑战的任务是使用目标本体论（例如DBPEDIA或WIKIDATA）预测答案类型。
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).
