Data Shapes in Action: Difference between revisions
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===Description=== | ===Description=== | ||
At the [https://www.sdir.no/ Norwegian Maritime Authority] (NMA), a pipeline for extracting context, concepts and relationships in regulatory documents, is running in production. This session will outline the application implementation. Together with technologies used as Natural Language Processing, RDF serialization, and the use of SHACL to describe regulatory requirements. Including several use cases for NMA's knowledge graph. | At the [https://www.sdir.no/en/ Norwegian Maritime Authority] (NMA), a pipeline for extracting context, concepts and relationships in regulatory documents, is running in production. This session will outline the application implementation. Together with technologies used as Natural Language Processing, RDF serialization, and the use of SHACL to describe regulatory requirements. Including several use cases for NMA's knowledge graph. | ||
Revision as of 09:01, 28 April 2022
Synergies of computational linguistics and RDF
Date: June 16, 2022
Time: Time: 17h CET (Berlin, Madrid, Zürich), 16h UTC London, 12pm New York EDT and 9am San Francisco PDT
Registration Count: 15
Speakers
Veronika Heimsbakk - Managing AI Engineer, Capgemini
https://www.linkedin.com/in/vheimsbakk/
Miriam Næss Jørstad - Senior Data Scientist, Capgemini
https://www.linkedin.com/in/mirnjor/
Description
At the Norwegian Maritime Authority (NMA), a pipeline for extracting context, concepts and relationships in regulatory documents, is running in production. This session will outline the application implementation. Together with technologies used as Natural Language Processing, RDF serialization, and the use of SHACL to describe regulatory requirements. Including several use cases for NMA's knowledge graph.
Registration