Knowledge Graphs & Large Language Model integration - Real world examples
Details
How to get the most out of your enterprise knowledge graph, common challenges to be aware of, solutions and expected benefits & business cases.
Welcome to the first Connected Data London meetup of 2024! Doors will open at 6.00pm for talks starting at 18.30.
As usual refreshments and food will be available courtesy of our generous sponsors Beamery & Connected Data London.
Special perk for attendees: be the first to know the dates and venue for the upcoming Connected Data London 2024 conference!
Talk & Speakers
1. Knowledge Graphs x LLMs for Human Resources: automating the (once) impossible
Kaan Karakeben, Lead Data Scientist, Beamery
Much has been written about the ability of LLMs and Knowledge Graphs to work hand in hand. On the one hand you have Large Language Models that provide previously unimaginable flexibility and computational intelligence to automate any problem. Yet, without a KG to underpin this knowledge and ensure grounding, LLMs are subject to providing misinformation.
This talk will discuss Beamery’s approach to using LLMs and proprietary AI to “automate the hard stuff” in the HR profession, and how this work is underpinned by KGs.
2. Leveraging LLM and Knowledge Graphs for ESG Analysis
Adam Wangrat, Lead Knowledge Graph Engineer, Neural Alpha
This talk explores how integrating Large Language Models (LLMs) and Knowledge Graphs can revolutionize Environmental, Social, and Governance (ESG) research, disclosure analysis, custom benchmarking and other requirements.
By combining the power of an LLM-based question-answering system with a Neo4j Knowledge Graph containing rich ESG-related data, we can enable more accurate, context-aware, and insightful responses to user queries about ESG factors. Through real-world examples and practical strategies, attendees will learn how this synergy can transform ESG analysis, driving informed decision-making and stakeholder engagement.
3. How Graph RAG and rules-based AI can power expert chatbots and other applications
Nick Form, CTO, Oxford Semantic TechnologiesCen Xi Toh, Knowledge Engineer, Oxford Semantic Technologies
This talk will show how to improve the accuracy of Large Language Models (LLM) by implementing a Retrieval Augmented Generation (RAG) approach using RDFox - a knowledge graph with an embedded semantic reasoner. We’ll demonstrate how this technology can power a chatbot to provide truthful, expert answers to even the most complex questions, using an example everyone can relate to - food!
The demo will concentrate on the use of an LLM in comprehending natural language, initiating function calls, and generating natural language responses. We’ll then cover how the use of rules and reasoning enhances the LLM's understanding and interpretation. The potential for other use cases across a variety of industries will also be explored.
Event timings
18:00 - 18:30 drinks, food & networking
18:30- 18:45 Welcome Beamery & Connected Data London
18:45- 19:15 First talk
19:15 - 19:45 Second talk
19:45 - 20:15 Third talk
20:20 - 21.00 Drinks/Networking
21.00 Event close
Address & building access
Beamery, HYLO, 105 Bunhill Row, London EC1Y 8LZ
Your details will be shared with our event sponsor, Beamery, for communication, health & safety purposes relating to the event only.
You'll get an email with a QR code from Beamery Hylo building reception 4 - 24 hours before the event. Scan the code for entry when you arrive inside the building. If you don't receive the email, reception can print a code on the day if you've registered for a ticket or bring a plus one.
Who is Beamery?
Beamery’s Talent Lifecycle Management platform brings together your data on candidates, employees and alumni.
We are an AI-powered platform that powers faster recruiting, successful internal mobility, smarter upskilling and more agile workforce planning so enterprise companies can improve the experience for all talent.
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Hear more at 👉Careers.Beamery.com