| Session
|
A look across the industry, Part 2
|
| Duration
|
1 hour
|
| Date/Time
|
25 Oct 2023 16:00 GMT
|
| 9:00am PDT/12:00pm EDT
|
| 4:00pm GMT/5:00pm CST
|
| Convener
|
Andrea Westerinen and Mike Bennett
|
Agenda
- Evren Sirin, Stardog CTO and lead for their new Voicebox offering
- Title: Stardog Voicebox: LLM-Powered Question Answering with Knowledge Graphs
- Abstract: Large Language Models (LLMs) and Generative AI technologies have caused a shift in all areas of information technology but especially for question answering use cases. Leveraging LLMs for question answering can help fully democratize enterprise analytics and data access. However, using LLMs with enterprise data bring significant challenges around security, privacy, accuracy, and explainabilty. In this talk we will present Stardog Voicebox which leverages an open-source foundational LLM to build, manage, and query knowledge graphs using ordinary language. The answers to user questions directly come from the knowledge graph providing complete traceability and access control. Stardog Voicebox combines statistical reasoning in the form of LLMs with logical reasoning in knowledge graphs providing a powerful hybrid reasoning system with a natural language interface.
- Yuan He, Key contributor to DeepOnto, a package for ontology engineering with deep learning
- Title: DeepOnto: A Python Package for Ontology Engineering with Deep Learning and Language Models
- Abstract: Integrating deep learning techniques, particularly language models (LMs), with knowledge representations like ontologies has raised widespread attention, urging the need for a platform that supports both paradigms. However, deep learning frameworks like PyTorch and Tensorflow are predominantly developed for Python programming, while widely-used ontology APIs, such as the OWL API and Jena, are primarily Java-based. To facilitate seamless integration of these frameworks and APIs, we present DeepOnto, a Python package designed for ontology engineering with deep learning. The package encompasses a core ontology processing module founded on the widely-recognized and reliable OWL API, encapsulating its fundamental features in a more “Pythonic” manner and extending its capabilities to incorporate other essential components including reasoning, verbalization, normalization, projection, taxonomy, and more. Building on this module, DeepOnto offers a suite of tools, resources, and algorithms that support various ontology engineering tasks, such as ontology alignment and completion, by harnessing deep learning methods, primarily pre-trained LMs.
Conference Call Information
- Date: Wednesday, 25 October 2023
- Start Time: 9:00am PDT / 12:00pm EDT / 6:00pm CEST / 5:00pm BST / 1600 UTC
- 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
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