Abstract The Semantic Web contains an enormous amount of information in the form of
knowledge bases (KB). To make this information available, many question answering (QA) …

A large number of published datasets (or sources) that follow Linked Data principles is
currently available and this number grows rapidly. However, the major target of Linked Data …

Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Recently, a large number of studies focus on semantically or syntactically …

RDF question/answering (Q/A) allows users to ask questions in natural languages over a
knowledge base represented by RDF. To answer a natural language question, the existing …

We propose a novel methodology to generate domain-specific large-scale question
answering (QA) datasets by re-purposing existing annotations for other NLP tasks. We …

Abstract Knowledge graphs have gained increasing popularity in the last decade in science
and technology. However, knowledge graphs are currently relatively simple to moderate …

Semantic Question Answering (SQA) removes two major access requirements to the
Semantic Web: the mastery of a formal query language like SPARQL and knowledge of a …

Abstract The Question Answering (QA) task aims to provide precise and quick answers to
user questions from a collection of documents or a database. This kind of IR system is sorely …

This article provides a comprehensive overview of the broad area of semantic search on text
and knowledge bases. In a nutshell, semantic search is “search with meaning”. This …

RDF question/answering (Q/A) allows users to ask questions in natural languages over a
knowledge base represented by RDF. To answer a national language question, the existing …