Crowdsourced Linked Data Question Answering with AQUACOLD - Collis, Nicholas; Frommholz, Ingo (2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 2021)
There is a need for Question Answering (QA) to return accurate answers to complex natural language questions over Linked Data, improving the accessibility of Linked Data (LD) search by abstracting the complexity of SPARQL whilst retaining its expressiveness. This work presents AQUACOLD, a LD QA system which harnesses the power of crowdsourcing to meet this need.