Knowledge graphs have emerged as a powerful tool for organizing and connecting large amounts of data, as they provide a structured representation of relationships and dependencies between different entities and concepts. They can allow you to get insight from patterns not previously visible in your data and make more informed decisions. However, developing a knowledge graph from scratch can be a daunting task. To overcome this challenge, enterprises can leverage the capabilities of generative AI to get started with semantic modeling faster.
How to Leverage Generative AI for Knowledge Modeling?
Generative AI empowers businesses to automate various business processes, improving efficiency and increasing employee productivity. Leveraging generative AI with a human in the loop, using the powerful Progress Semaphore technology, can deliver better overall results and make you more productive in the creation, enrichment and management of your semantic models.
Start generating knowledge graphs with the power of generative AI and Semaphore. During this webinar, we will show you how you can:
- Leverage generative AI for the development of knowledge models.
- Enrich, link and manage semantic models.
- Create SPARQL queries and SHACL (Shapes Constraint Language) shapes with generative AI and then manage and run them.
Watch this on-demand recap with Senior Enterprise Account Manager, Doug Dunn, as he discusses the importance of semantic models and how companies can enhance their value by leveraging generative AI. Also presenting during this session is Lance Thieshen, Senior Sales Engineer, who demonstrates the combined power of generative AI and Semaphore to simplify the creation and management of semantic knowledge models.
For more information or to request a demo, contact us.