Data Shapes in Action: Difference between revisions
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Date: June 16, 2022 | Date: June 16, 2022 | ||
Time: Time: 17h CET (Berlin, Madrid, Zürich), | Time: Time: 16h UTC London, 17h CET (Berlin, Madrid, Zürich), 11am New York EDT and 8am San Francisco PDT | ||
Registration Count: | Registration Count / Attendees: 110/57 | ||
<hr> | <hr> | ||
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Miriam Næss Jørstad - Senior Data Scientist, Capgemini <br> | Miriam Næss Jørstad - Senior Data Scientist, Capgemini <br> | ||
https://www.linkedin.com/in/mirnjor/ | https://www.linkedin.com/in/mirnjor/ | ||
<center><youtube>https://youtu.be/8K3XYTdc3ag</youtube></center> | |||
===Description=== | ===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. | 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. | ||
===Shared Event Notes=== | |||
https://docs.google.com/document/d/1V9YRKYUDXQeCCGALtsTzxnPSvuL4WSsBBcpDtz1PYSM/edit?usp=sharing | |||
Session-Type: Technology - Project | |||
Session-Level: Introduction - Intermediate | |||
[[Category:Event]] | [[Category:Event]] | ||
Latest revision as of 08:15, 21 June 2022
Synergies of computational linguistics and RDF
Date: June 16, 2022
Time: Time: 16h UTC London, 17h CET (Berlin, Madrid, Zürich), 11am New York EDT and 8am San Francisco PDT
Registration Count / Attendees: 110/57
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.
https://docs.google.com/document/d/1V9YRKYUDXQeCCGALtsTzxnPSvuL4WSsBBcpDtz1PYSM/edit?usp=sharing
Session-Type: Technology - Project Session-Level: Introduction - Intermediate