Question Answering over Linked Data (QALD-7) Challenge at ESWC 2017
May 28 - June 1
The past years have seen a growing amount of research on question answering (QA) over Semantic Web data, shaping an interaction paradigm that allows end users to profit from the expressive power of Semantic Web standards while at the same time hiding their complexity behind an intuitive and easy-to-use interface. At the same time the growing amount of data has led to a heterogeneous data landscape where QA systems struggle to keep up with the volume, variety and veracity of the underlying knowledge.
The Question Answering over Linked Data (QALD) challenge aims at providing an up-to-date benchmark for assessing and comparing state-of-the-art-systems that mediate between a user, expressing his or her information need in natural language, and RDF data. It thus targets all researchers and practitioners working on querying Linked Data, natural language processing for question answering, multilingual information retrieval and related topics. The main goal is to gain insights into the strengths and shortcomings of different approaches and into possible solutions for coping with the large, heterogeneous and distributed nature of Semantic Web data.
QALD has a 6-year history of developing a benchmark that is increasingly being used as standard evaluation benchmark for question answering over Linked Data. Overviews of the past instantiations of the challenge are available from the CLEF Working Notes as well as ESWC proceedings: QALD-6, QALD-5, QALD-4, QALD-3.
Since many of the topics relevant for QA over Linked Data lie at the core of ESWC (Multilinguality, Semantic Web, Human-Machine-Interfaces), we will run the 7th instantiation of QALD again at ESWC 2017. HOBBIT project guarantees a controlled setting involving rigorous evaluations via its platform.