Natural Language Processing Knowledge Graph (NLP-KG)

 A Knowledge Graph for Natural Language Processing Research

Web Application

https://nlpkg.sebis.cit.tum.de 

Motivation

• Scientific knowledge is usually available in large quantities as unstructured texts.
• This makes getting an overview of new or unknown scientific fields difficult.
• Furthermore, it is challenging to stay up-to-date with newly published research.
• This is a growing challenge in NLP, where new research is being published at an exponential growth rate.
• Structuring the NLP knowledge by linking semantically related NLP fields offers the potential for enhanced exploration of the domain.

Objective

The NLP knowledge graph is an approach to tackle the information overload challenge of researchers. It aims to help researchers in obtaining an overview of NLP-related topics and find relevant papers more efficiently. A user-friendly web application and a natural language conversational interface will be developed to make the NLP knowledge graph easy to use.

Resources

NLP-KG Poster: 230629 Schopf NLP-KG Poster.pdf

Research Activities