AI in Action Technology
Talk to Your Graph Client for GraphDB
Learn how to develop a Talk to Your Graph (TTYG) client by integrating GraphDB and the OpenAI Assistants API
Pavel MihaylovTechnology
Pavel Mihaylov
AI in Action Technology
How Far We Can Go with GenAI as an Information Extraction Tool
How we used Ontotext GraphDB and LLMs to improve CV selection
Anna Aksenova
Petar Mitankin
Filip Dimitrov
Stefan Nikolov
AI in Action Technology
My Dear Watson, it is Great to Have Someone to Talk to
Join us to learn how we empower users to sift through a large pool of data with the help of a trusted assistant – the GraphDB 10.8 Talk To Your Graph agent.
Nedelina Mitankina
Andrey Tagarev
Technology
Using Entity Linking to Turn Your Graph into a Knowledge Graph
Ontotext’s Tag service can recognize entities and assign standard identifiers that let you enrich your graphs.
Bob DuCharme
Technology
Deploying Ontotext GraphDB on Azure
Read this post providing a guide for deploying an Ontotext GraphDB high-availability cluster in your own Azure account
Ivo Rusev
AI in Action Technology
Leveraging Ontotext’s Eligibility Design Assistant for Effective Patient Population Selection
Combining highly normalized knowledge graphs with large language models for quick and reliable selection of clinical trial eligibility criteria
Ivelina Nikolova
Katerina Serafimova
Georgi Iliev
Todor Primov
AI in Action Technology
A Triple Store RAG Retriever
How we used Ontotext GraphDB’s vector capabilities to build a simple RAG retriever over a Knowledge Graph, using open, offline LLM models
Matteo Casu
Technology
Integrating GraphDB with Relational Database Systems
Learn how to treat an RDF repository like relational data — or treat a relational database like RDF
Bob DuCharme
Technology
Migrating From LPG to RDF Graph Model
This post discusses the LPG-RDF vis-a-vis graph models and why enterprises should invest in knowledge graphs with RDFs for their data management practices
Sumit Pal