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Talk to Your Graph Client for GraphDB
Introduction Since I became the product manager of GraphDB, I was expected to stop writing code but I couldn’t help it. It’s certainly unorthodox but I strongly believe this makes the product better....
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How Far We Can Go with GenAI as an Information Extraction Tool
Introduction In the real world, obtaining high-quality annotated data remains a challenge. Generative AI (GenAI) models, such as GPT-4, offer a promising solution, potentially reducing the dependency...
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My Dear Watson, it is Great to Have Someone to Talk to
Introduction Whether you are in the position of Sherlock Holmes, a data analyst, or a business manager, it’s always useful to augment your vision of the available data to derive better insights. An...
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Semantization of Regulatory Documents in AECO
Introduction Unlike our not-so-distant hunter-gatherer ancestors, today most of us live in a built environment. According to the World Bank, about 56% of the world’s population (4.4 billion...
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Deploying Ontotext GraphDB on AWS
Even the best database depends on running on solid hardware. And the cloud gives you flexibility at a reasonable price. We have already explained how to deploy GraphDB in a generic environment and on...
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Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s...
It’s no secret that data scientists and researchers spend 80% of their time on the less glamorous tasks of chasing down data, cleaning it up, and making sure it’s not full of nonsense. Researchers in...
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Using Entity Linking to Turn Your Graph into a Knowledge Graph
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. What’s the difference between a graph and a...
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Deploying Ontotext GraphDB on Azure
Our blog post GraphDB Cluster Deployment Strategies explained how to deploy a high-availability GraphDB cluster. This can be done both on-premises and in the cloud. Ontotext collaborates with major...
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Leveraging Ontotext’s Eligibility Design Assistant for Effective Patient...
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Drug discovery is an ever-growing field of...
View ArticleClik here to view.
Deploying Ontotext GraphDB on AWS
Even the best database depends on running on solid hardware. And the cloud gives you flexibility at a reasonable price. We have already explained how to deploy GraphDB in a generic environment and on...
View ArticleClik here to view.
Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s...
It’s no secret that data scientists and researchers spend 80% of their time on the less glamorous tasks of chasing down data, cleaning it up, and making sure it’s not full of nonsense. Researchers in...
View ArticleClik here to view.
Using Entity Linking to Turn Your Graph into a Knowledge Graph
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. What’s the difference between a graph and a...
View ArticleClik here to view.
Deploying Ontotext GraphDB on Azure
Our blog post GraphDB Cluster Deployment Strategies explained how to deploy a high-availability GraphDB cluster. This can be done both on-premises and in the cloud. Ontotext collaborates with major...
View ArticleClik here to view.
Leveraging Ontotext’s Eligibility Design Assistant for Effective Patient...
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Drug discovery is an ever-growing field of...
View ArticleClik here to view.
A Triple Store RAG Retriever
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Motivations and Setup In the last year or so the...
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Integrating GraphDB with Relational Database Systems
As you might guess from its name, GraphDB stores data in a graph data structure, which is much more flexible than the rigid table structures used by relational database managers. Relational databases...
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Migrating From LPG to RDF Graph Model
In the first part of this series, we discussed the basics of LPG and RDF graph models and their pros and cons in building knowledge graphs. The second part of the series discusses how to migrate LPG...
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Okay, RAG… We Have a Problem
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. In previous publications, we introduced the...
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Using GraphDB’s Natural Language Interface to Talk with Your Content
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Ontotext is a knowledge graph company. We use...
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Event Extraction Based on Fine-Tuned Text2Event Transformer Speeds up the...
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Disinformation is on the rise and fact-checkers...
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