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NLP-Knowledge-Graph is an open educational repository that collects resources, research materials, and tutorials focused on the intersection of natural language processing and knowledge graph technologies. The project aims to help researchers and developers understand how structured knowledge representations can enhance language processing systems. It includes curated materials covering key topics such as knowledge graph construction, entity recognition, relation extraction, graph embeddings, and semantic reasoning. By combining NLP techniques with graph-based data models, knowledge graphs allow systems to represent complex relationships between entities and improve tasks such as question answering, information retrieval, and recommendation systems. The repository aggregates research papers, technical articles, tutorials, and open-source tools related to these areas.
Features
- Curated collection of resources on NLP and knowledge graph research
- Guides covering entity recognition and relation extraction techniques
- References to graph embedding and semantic reasoning methods
- Compilation of academic papers and technical tutorials
- Structured organization of knowledge graph learning materials
- Educational resource for researchers and AI practitioners
Project Samples
