The recent surge of interest in explainability in artificial intelligence (XAI) is propelled by not
only technological advancements in machine learning but also by regulatory initiatives to …

Classifying nodes in knowledge graphs is an important task, eg, for predicting missing types
of entities, predicting which molecules cause cancer, or predicting which drugs are …

Several applications, such as text-to-SQL and computational fact checking, exploit the
relationship between relational data and natural language text. However, state of the art …

This paper presents a survey on multilingual Knowledge Graph Question Answering
(mKGQA). We employ a systematic review methodology to collect and analyze the research …

The RDF-to-text task has recently gained substantial attention due to continuous growth of
Linked Data. In contrast to traditional pipeline models, recent studies have focused on …

This paper focuses on the generation of natural language questions based on SPARQL
queries, with an emphasis on conversational use cases (follow-up question-answering). It …

The paper presents recent work on the design and development of AI chatbots for museums
using Knowledge Graphs (KGs). The utilization of KGs as a key technology for implementing …

In the future, robots are expected to autonomously interact and/or collaborate with humans,
who will increase the uncertainty during the execution of tasks, provoking online adaptations …

Ontology lexicalization aims to provide information about how the elements of an ontology
are verbalized in a given language. Most ontology lexicalization techniques require labeled …

Software with natural-language user interfaces has an ever-increasing importance.
However, the quality of the included Question Answering (QA) functionality is still not …