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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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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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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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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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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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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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