Build Knowledge Graphs from Unstructured Data: Join Our Talk!

Join us for a talk about "How To Construct Knowledge Graphs from Unstructured Data" hosted by GraphGeeks.org https://live.zoho.com/PBOB6fvr6c Wed Aug 14, 09:00 US Pacific We'll walk you through the broader practices of building and updating knowledge graphs, while leveraging open source libraries for state-of-the-art tooling (hint: lots of transformer models, not LLMs). Techniques such as "Graph-enhanced RAG" help mitigate hallucinations in the AI apps downstream. This is especially important for use in highly regulated environments where KG construction must be accountable, explainable, based on evidence, etc. If you've been hearing terms such as "named entity recognition", "entity resolution", "lexical graph", "entity linking", "textgraphs", "semantic random walks", "embeddings", "relation extraction", "semantic layer", and so on, and ever wondered how these fit together into practical solutions ... join us, that's what we'll cover! In other words, a full deconstruction of the elements of KG construction leading into GraphRAG. Some component libraries include: spaCy, NetworkX, Pandas, GLiNER, GLiREL, ReLIK, Pydantic, LanceDB -- and if you want a sneak peek at the code: https://github.com/DerwenAI/strwythura BTW, the graph visualization shown here is what we'll construct from articles about linkages between eating processed red meat frequently and the risk of developing dementia. We'll build out a KG and vector DB suitable for GraphRAG grounding in an LLM chatbot or agent. #ERKG #KnowledgeGraph #UnstructuredData #DataScience #MachineLearning #TechWorkshops