Using LLM as an intermediate layer to take natural language text inputs and create Cypher queries on the graph to return knowledge makes querying the graph more intuitive and user-friendly.

The Future Of LLMs And Knowledge Graphs Both LLMs and knowledge graphs are complex, state-of-the-art technologies, and linking them within a single application is a major challenge.

Knowledge graphs offer a powerful repository of direct, traceable, contextual knowledge of entities and knowledge structures for RAG pipelines. Your LLM will indeed wish you had used a knowledge ...

Knowledge graph startup Diffbot Technologies Corp., which maintains one of the largest online knowledge indexes, is looking to tackle the problem of hallucinations in artificial intelligence ...

LangGraph has been used to create a multi-agent large language model (LLM) coding framework. This framework is designed to automate various ...

In a paper published in Journal of Geo-information Science, a group of researchers pioneered a new paradigm by leveraging large language models (LLMs) in constructing typhoon disaster knowledge graphs ...

data.world’s benchmark report reveals 3x uptick in LLM response accuracy over SQL databases, when those answers were backed by a Knowledge Graph. Complex business questions around metrics, KPIs, and ...

The Bulgarian graph database startup Graphwise today announced a major upgrade to its flagship GraphDB tool, adding new features aimed at boosting enterprise knowledge management and creating a more ...