Automatic Skill Generation for Knowledge Graph Question Answering

Maria Angela Pellegrino, Mario Santoro, Vittorio Scarano, Carmine Spagnuolo

Keywords: Question Answering, Knowledge Graphs, Virtual Assistant, Software Framework

TL;DR: community shared software framework to automatically generate virtual assistant extensions for knowledge graph question-answering

Abstract:

Knowledge Graphs are a critical source for Question Answering, but their potential may be threatened due to the complexity of their query languages, such as SPARQL. On the opposite side, Virtual Assistants have witnessed an extraordinary interest as they enable users to pose questions in natural language. Many companies and researchers have combined Knowledge Graphs and Virtual Assistants, but no one has provided end-users with a generic methodology to generate extensions for automatically querying knowledge graphs.
Thus, we propose a community shared software framework to create custom extensions to query knowledge graphs by virtual assistants, unlocking the potentialities of the Semantic Web technologies by bringing knowledge graphs in the ``\textit{pocket}" of everyone, accessible from smartphones or smart speakers.