While the amount of knowledge available as linked data grows, so does the need for
providing end users with access to this knowledge. Especially question answering systems …

For humans, understanding a natural language sentence or discourse is so effortless that
we hardly ever think about it. For machines, however, the task of interpreting natural …

The third edition of the open challenge on Question Answering over Linked Data (QALD-3)
has been conducted as a half-day lab at CLEF 2013. Differently from previous editions of the …

With the emergence of the linked data initiative and the rapid development of RDF
(Resource Description Format) datasets, several approaches have recently been proposed …

Abstract Natural Language Generation (NLG) is concerned with transforming given content
input into a natural language output, given some communicative goal. Although this input …

A core step in statistical data-to-text generation concerns learning correspondences
between structured data representations (eg, facts in a database) and associated texts. In …

The increasing amount of machinereadable data available in the context of the Semantic
Web creates a need for methods that transform such data into human-comprehensible text …

This paper provides a dependency based framework for converting natural language to
SPARQL. We present a tool known as PAROT (which echos answers from ontologies) which …

Abstract The Semantic Web (SW) is now made of billions of triples, which are available as
Linked Open Data (LOD) or as RDF stores. The SPARQL query language provides a very …

As the body of knowledge available as linked data grows, so does the need to provide
methods that make this knowledge accessible for humans. Such methods usually require …