4^th International Workshop on Natural Language Processing for Knowledge Graph Construction

Knowledge graphs (KG) are becoming increasingly popular, at the heart of Gartner's emerging tech impact radar, especially as a complementary theme for addressing the challenges of recent advances in natural language processing (NLP) with large language models related to responsible AI such as fairness, transparency, accountability, and explainability. Sir Tim Berners-Lee's seminal work “Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web”, envisioned a World Wide Web where information is not only accessible but structured, allowing machines to interpret data meaningfully. This vision laid the groundwork for technologies such as RDF (Resource Description Framework) and OWL (Web Ontology Language), which serve as foundational components for modern KGs. However, the process of building domain-specific KGs from extensive text corpora is highly complex and resource-intensive, requiring careful task design for entity recognition, disambiguation, and relationship extraction, among others. These tasks are essential to ensure accuracy and relevance in knowledge representation, but they pose considerable challenges. Addressing these complexities is crucial for the continued advancement and application of KGs across domains. In this context, the 4^th NLP4KGC workshop is held to create a collaborative platform for researchers, practitioners, and industry experts in NLP and KG construction. Following the success and growing community engagement in the previous three editions, this year's workshop aims to deepen collaboration and encourage innovative solutions in this rapidly evolving field. The 4^th NLP4KGC will continue to bridge academia and industry, fostering the exchange of insights, tools, and methodologies at the intersection of NLP and KG development. The 4^th NLP4KGC will consist of five accepted papers and three keynotes from distinguished speakers.