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{| class="wikitable" style="float:right; margin-left: 10px;" border="1" cellpadding="10"
= [[OntologySummit2024|Ontology Summit 2024]] =
|-
! scope="row" | Session
| [[session::Demos of information extraction via hybrid systems]]
|-
! scope="row" | Duration
| [[duration::1 hour]]
|-
! scope="row" rowspan="3" | Date/Time
| [[has date::1 Nov
2023 16:00 GMT]]
|-
| 9:00am PDT/12:00pm EDT
|-
| 4:00pm GMT/5:00pm CET
|-
! scope="row" | Convener
| [[convener::AndreaWesterinen|Andrea Westerinen]] and [[convener::MikeBennett|Mike Bennett]]
|}


= [[OntologySummit2024|Ontology Summit 2024]] {{#show:{{PAGENAME}}|?session}} =
The [[OntologySummit|Ontology Summit]] is an annual series of events that involves the ontology community and communities related to each year's theme chosen for the summit. The Ontology Summit was started by Ontolog and NIST, and the program has been co-organized by Ontolog and NIST along with the co-sponsorship of other organizations that are supportive of the Summit goals and objectives.


== Agenda ==
== Purpose ==
* [[AndreaWesterinen|Andrea Westerinen]], Creator of [https://github.com/ontoinsights/deep_narrative_analysis DNA, Deep Narrative Analysis]
As part of Ontolog’s general advocacy to bring ontology science and related engineering into the mainstream, we endeavor to  facilitate discussion and knowledge sharing amongst stakeholders and interested parties relevant to the use of ontologies. The results will be synthesized and summarized in the form of the Ontology Summit 2024 Communiqué, with expanded supporting material provided on the web and in journal articles.
** '''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.
* [[PrasadYalamanchi|Prasad Yalamanchi]], ''Lead Semantics CEO''


== Conference Call Information ==
= Process and Deliverables =
* Date: '''Wednesday, 1 November 2023'''
Similar to our last seventeen summits, this [[OntologySummit2024|Ontology Summit 2024]] will consist of virtual discourse (over our archived mailing lists), virtual presentations and panel sessions as part of recorded video conference calls.
* Start Time: 9:00am PDT / 12:00pm EDT / 5:00pm CET / 4:00pm GMT / 1600 UTC
As in prior years the intent is to provide some synthesis of ideas and draft a communique summarizing major points.
** Note that Daylight Saving Time has ended in Europe but not in the US or Canada.
This year will begin with a Fall Series in October and November; the main summit will begin in February.
** ref: [http://www.timeanddate.com/worldclock/fixedtime.html?month=11&day=1&year=2023&hour=12&min=00&sec=0&p1=179 World Clock]
* Expected Call Duration: 1 hour
{{:OntologySummit2024/ConferenceCallInformation}}


== Participants ==
Meetings are at Noon US/Canada Eastern Time on Wednesdays and last about an hour.


== Discussion ==
== Fall Series on Ontologies and Large Language Models: Related but Different ==


== Resources ==
Fall Series Co-Chairs:  Andrea Westerinen and Mike Bennett


== Previous Meetings ==
{{:OntologySummit2024/Theme}}
{{#ask: [[Category:OntologySummit2024]] [[Category:Icom_conf_Conference]] [[<<ConferenceCall_2023_11_01]]
        |?|?Session|mainlabel=-|order=desc|limit=3}}
== Next Meetings ==
{{#ask: [[Category:OntologySummit2024]] [[Category:Icom_conf_Conference]] [[>>ConferenceCall_2023_11_01]]
        |?|?Session|mainlabel=-|order=asc|limit=3}}


= Schedule =
== Fall Series ==
* [[ConferenceCall_2023_10_04|4 October 2023]] ''Kickoff/Overview'', '''[[AndreaWesterinen|Andrea Westerinen]]''' and '''[[MikeBennett|Mike Bennett]]'''
* [[ConferenceCall_2023_10_11|11 October 2023]] ''Setting the stage'', '''[[DeborahMcGuinness|Deborah McGuinness]]'''
** Rennselaer Tetherless World Senior Constellation Chair
** Professor of Computer Science, Cognitive Science, and Industrial and Systems Engineering
** Expert in knowledge representation, reasoning languages and systems
* [[ConferenceCall_2023_10_18|18 October 2023]] ''A look across the industry, Part 1''
** '''Kurt Cagle''', Author of the [https://thecaglereport.com/ Cagle Report]
** '''Tony Seale''', Knowledge graph architect and thought leader ([https://www.linkedin.com/in/tonyseale/?originalSubdomain=uk LinkedIn])
* [[ConferenceCall_2023_10_25|25 October 2023]] ''A look across the industry, Part 2''
** '''Evren Sirin''', Stardog CTO and lead for their new [https://www.stardog.com/categories/voicebox/ Voicebox] offering
** '''Yuan He''', Key contributor to [https://github.com/KRR-Oxford/DeepOnto DeepOnto], a package for ontology engineering with deep learning
* [[ConferenceCall_2023_11_01|1 November 2023]] ''Demos of information extraction via hybrid systems''
** '''[[AndreaWesterinen|Andrea Westerinen]]''', [https://github.com/ontoinsights/deep_narrative_analysis Deep Narrative Analysis]
** '''[[PrasadYalamanchi|Prasad Yalamanchi]]''', [https://leadsemantics.com/ Lead Semantics CTO]
* [[ConferenceCall_2023_11_08|8 November 2023]] ''Broader thoughts''
** '''[[AnatolyLevenchuk|Anatoly Levenchuk]]''', Hybrid reasoning, the scope of knowledge, and what is beyond ontologies?
** '''[[JohnSowa|John Sowa]]''' and '''[[ArunMajumdar|Arun Majumdar]]''', LLMs, ontologies, and formal systems
* [[ConferenceCall_2023_11_15|15 November 2023]] Discussion and Synthesis, including questions for the full summit
= Resources =
* [[OntologySummit2024/ConferenceCallInformation|Conference Call Information]]
* [http://bit.ly/34DOmRV Ontology Summit YouTube Channel]
[[Category:OntologySummit]]
[[Category:OntologySummit2024]]
[[Category:OntologySummit2024]]
[[Category:Icom_conf_Conference]]
[[Category:Occurrence| ]]

Revision as of 14:28, 24 October 2023

Ontology Summit 2024

The Ontology Summit is an annual series of events that involves the ontology community and communities related to each year's theme chosen for the summit. The Ontology Summit was started by Ontolog and NIST, and the program has been co-organized by Ontolog and NIST along with the co-sponsorship of other organizations that are supportive of the Summit goals and objectives.

Purpose

As part of Ontolog’s general advocacy to bring ontology science and related engineering into the mainstream, we endeavor to facilitate discussion and knowledge sharing amongst stakeholders and interested parties relevant to the use of ontologies. The results will be synthesized and summarized in the form of the Ontology Summit 2024 Communiqué, with expanded supporting material provided on the web and in journal articles.

Process and Deliverables

Similar to our last seventeen summits, this Ontology Summit 2024 will consist of virtual discourse (over our archived mailing lists), virtual presentations and panel sessions as part of recorded video conference calls. As in prior years the intent is to provide some synthesis of ideas and draft a communique summarizing major points. This year will begin with a Fall Series in October and November; the main summit will begin in February.

Meetings are at Noon US/Canada Eastern Time on Wednesdays and last about an hour.

Fall Series on Ontologies and Large Language Models: Related but Different

Fall Series Co-Chairs: Andrea Westerinen and Mike Bennett

Neuro-Symbolic Techniques for and with Ontologies and Knowledge Graphs

The summit will survey current techniques that combine neural network machine learning with symbolic methods, especially methods based on ontologies and knowledge graphs.

Ontologies are representations of a knowledge domain. They define the concepts, relationships, properties, axioms and rules within that domain, providing a framework that enables a deep understanding of that subject area. Knowledge graphs are structured representations of semantic knowledge that are stored in a graph. Ontologies and knowledge graphs are used to enable machine reasoning and semantic understanding, allowing a system to draw inferences and to derive new information and relationships between entities.

Neural network and other machine learning models, such as LLMs, are trained on large corpora, learning the patterns and connections between words and images. Hence, although their “knowledge base” is broad, it is also sometimes incorrect and/or biased, and don't explicitly understand the semantics or relationships in that content.

Consequently, neural network and traditional AI techniques are complementary. The Fall Series of the summit explored the similarities and distinctions between ontologies and LLMs, as well as how they can be used together. The Main Summit Series will examine the more general topic of neuro-symbolic techniques, especially how one can leverage the complementary benefits of neural networks and of ontologies and knowledge graphs.

Main Series Tracks

  • Track A. Foundations and Architectures
  • Track B. Large Language Models, Ontologies and Knowedge Graphs
  • Track C. Applications
  • Track D. Risks and Ethics

Schedule

Fall Series

Resources