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ConferenceCall 2023 11 01: Difference between revisions

Ontolog Forum

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* [[PrasadYalamanchi|Prasad Yalamanchi]], [https://leadsemantics.com/ Lead Semantics] CTO
* [[PrasadYalamanchi|Prasad Yalamanchi]], [https://leadsemantics.com/ Lead Semantics] CTO
** '''Title:''' Harvest Knowledge From Language - Harness the power of Large Language Models and Semantic Technology
** '''Title:''' Harvest Knowledge From Language - Harness the power of Large Language Models and Semantic Technology
** '''Abstract:''' Language (both text and voice) holds much of the accessible knowledge to humans. It is also the best store of the collective human knowledge. Historically, accessing this knowledge, was manual and up until recent times has progressed to varying degrees of semi-automated methods! But, with the advent of Language Models and particularly Large Language Models in the last couple of years, a fully automated access to knowledge carried in language is now becoming a reality! TextDistil, the software product from Lead Semantics applies LLMs and Ontologies to extract computable knowledge in the form of RDF triples from Text.


== Conference Call Information ==
== Conference Call Information ==

Revision as of 16:09, 24 October 2023

Session Demos of information extraction via hybrid systems
Duration 1 hour
Date/Time 1 Nov

2023 16:00 GMT

9:00am PDT/12:00pm EDT
4:00pm GMT/5:00pm CET
Convener Andrea Westerinen and Mike Bennett

Ontology Summit 2024 Demos of information extraction via hybrid systems

Agenda

  • Andrea Westerinen, Creator of DNA, Deep Narrative Analysis
    • Title: Populating Knowledge Graphs: The Confluence of Ontology and Large Language Models
    • Abstract: Ontology-based Knowledge Graphs (KGs) stand at the forefront of semantic data representation, providing structured views of the data in complex domains. Traditionally, populating these KGs from unstructured text involved convoluted natural language analyses and custom code, but the environment has changed with the use of Large Language Models (LLMs). This talk explores one use case - the population of a KG from news articles. The evolution of the application from employing spaCy APIs to OpenAI is described, and the current (open-source) implementation discussed. Implementation issues such as sourcing the data, LLM prompts, mapping the LLM responses onto the ontology, and populating the knowledge graph are overviewed.
  • Prasad Yalamanchi, Lead Semantics CTO
    • Title: Harvest Knowledge From Language - Harness the power of Large Language Models and Semantic Technology
    • Abstract: Language (both text and voice) holds much of the accessible knowledge to humans. It is also the best store of the collective human knowledge. Historically, accessing this knowledge, was manual and up until recent times has progressed to varying degrees of semi-automated methods! But, with the advent of Language Models and particularly Large Language Models in the last couple of years, a fully automated access to knowledge carried in language is now becoming a reality! TextDistil, the software product from Lead Semantics applies LLMs and Ontologies to extract computable knowledge in the form of RDF triples from Text.

Conference Call Information

  • Date: Wednesday, 1 November 2023
  • Start Time: 9:00am PDT / 12:00pm EDT / 5:00pm CET / 4:00pm GMT / 1600 UTC
    • Note that Daylight Saving Time has ended in Europe but not in the US or Canada.
    • ref: World Clock
  • Expected Call Duration: 1 hour
  • Video Conference URL: https://bit.ly/48lM0Ik
    • Conference ID: 876 3045 3240
    • Passcode: 464312

The unabbreviated URL is: https://us02web.zoom.us/j/87630453240?pwd=YVYvZHRpelVqSkM5QlJ4aGJrbmZzQT09

Participants

Discussion

Resources

Previous Meetings

 Session
ConferenceCall 2023 10 25A look across the industry, Part 2
ConferenceCall 2023 10 18A look across the industry, Part 1
ConferenceCall 2023 10 11Setting the stage
... further results

Next Meetings

 Session
ConferenceCall 2023 11 08Broader thoughts
ConferenceCall 2023 11 15Synthesis
ConferenceCall 2024 02 21Overview
... further results