Automatic Question Answering (QA) has been successfully applied in various domains such
as search engines and chatbots. Biomedical QA (BQA), as an emerging QA task, enables …

Knowledge from diverse application domains is organized as knowledge graphs (KGs) that
are stored in RDF engines accessible in the web via SPARQL endpoints. Expressing a well …

The recent success of Large Language Models (LLM) in a wide range of Natural Language
Processing applications opens the path towards novel Question Answering Systems over …

We present BYOKG, a universal question-answering (QA) system that can operate on any
knowledge graph (KG), requires no human-annotated training data, and can be ready to use …

The problem of natural language processing over structured data has become a growing
research field, both within the relational database and the Semantic Web community, with …

With the advent of natural language enabled applications, there has been a growing
appetite for conversational question answering systems. This demand is being largely …

With the recent spike in the number and availability of Large Language Models (LLMs), it
has become increasingly important to provide large and realistic benchmarks for evaluating …

A knowledge graph (KG) is a multidirectional labelled graph used for the graphical
representation of knowledge where each node represents an entity, and the edge …

Researchers have developed several question answering systems that interpret the user's
natural language question and fetches the answer from knowledge graphs. One of the main …

What we Learned About the Data Science Life Cycle: Best Practices and Open Research
Challenges Page 1 1 What we Learned About the Data Science Life Cycle: Best Practices and …