Improving Retrieval Augmented Generation accuracy with GraphRAG | Amazon Web Services
Lettria, an AWS Partner, demonstrated that integrating graph-based structures into RAG workflows improves answer precision by up to 35% compared to vector-only retrieval methods. In this post, we explore why GraphRAG is more comprehensive and explainable than vector RAG alone, and how you can use this approach using AWS services and Lettria.
PG-Schema: Schemas for Property Graphs | Proceedings of the ACM on Management of Data
Property graphs have reached a high level of maturity, witnessed by multiple robust
graph database systems as well as the ongoing ISO standardization effort aiming at
creating a new standard Graph Query Language (GQL). Yet, despite documented demand,
...
OpenSPG (Semantic-Enhanced Programmable Graph) is a new generation of enterprise knowledge graph (EKG) engine, bidirectionally enhanced by LLMs and knowledge graphs
OpenSPG (Semantic-Enhanced Programmable Graph) is a new generation of enterprise knowledge graph (EKG) engine, bidirectionally enhanced by LLMs and knowledge…
OpenSPG (Semantic-Enhanced Programmable Graph) is a new generation of enterprise knowledge graph (EKG) engine, bidirectionally enhanced by LLMs and knowledge graphs
RDF Sketch, a complete rewrite of our VS Code extension for visualizing and exploring RDF files
🎅 Santa Came Early with RDF Sketch🎅 This holiday season, we’re excited to share a special gift from Zazuko to the community: RDF Sketch, a… | 11 comments on LinkedIn
RDF Sketch, a complete rewrite of our VS Code extension for visualizing and exploring RDF files
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph…
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
Panama Papers Investigation using Entity Resolution and Entity Linking
This article demonstrates how developers or investigative journalists can use Senzing entity resolution (ER) to work with unstructured documents. In particular, given that ER has been used with structured data sources to construct a domain-specific KG, the results of ER can be leveraged to customise entity linking (EL) downstream, for example using spaCy — as an alternative to off-the-shelf EL sources such as DBPedia.
Enterprise GraphRAG: Building Production-Grade LLM Applications with Knowledge Graphs
Enterprise GraphRAG: Building Production-Grade LLM Applications with Knowledge Graphs Let’s dive into the numbers: Real-World Results Implementing GraphRAG…
Enterprise GraphRAG: Building Production-Grade LLM Applications with Knowledge Graphs
LazyGraphRAG sets a new standard for GraphRAG quality and cost
Introducing a new approach to graph-enabled RAG. LazyGraphRAG needs no prior summarization of source data, avoiding prohibitive up-front indexing costs. It’s inherently scalable in cost and quality across multiple methods and search mechanisms: