Harnessing LLMs for Enhanced Query Generation in Knowledge Graphs

Dean Allemang Dean Allemang literally wrote the book on the semantic web. "Semantic Web for the Working Ontologist" is now in its third edition. In the book, Dean and his co-authors, James Hendler and Fabien Gandon, show how to apply web standards to build a meaningful web of global, connected knowledge. More recently, Dean has conducted research with his colleagues at data.world that shows how using knowledge graphs can triple the accuracy of LLM-based question-answering systems. We talked about: his role as a principal solutions architect at data.world the meaning of the "semantic web" and its intent of sharing meaning across the web the long history of knowledge representation and how the connectedness of the semantic web adds to it the crucial difference between documents about things and the strings that describe them the contrast between the persistent nature of enterprise data and the ephemerality of the applications that use the data the power of the simple structure of RDF, its mathematical affordances, and the ease of distribution it permits the impact of newer AI tech on knowledge graph building and querying the research that he and Juan Sequeda have conducted that shows how using knowledge graphs can triple the accuracy of LLM-based question-answering systems his thoughts on the yet-to-be-resolved one-way or two-way ontology question the crucial role of trust in AI and how replacing LLMs with knowledge graphs as the point of contact in AI systems could build more trust Dean's bio Dean Allemang has been active in the field of Artificial Intelligence (AI) since the 1980s. With a notable emphasis on Semantic Web, he is the author of the book "Semantic Web for the Working Ontologist." His passion for understanding and implementing knowledge graphs led to a significant publication about using LLMs to answer queries over structured data, which introduced a new benchmark for evaluation. In his current role as a Principal Solutions Architect at data.world, he contributes extensively to the development of the AI Context Engine product, which is inspired by his recent research (with Juan Sequeda and Bryon Jacob), and underscores his commitment to practical application of theoretical principles. For a span of about a decode, Dean operated as an independent consultant, utilizing knowledge graph solutions to address challenges in industries such as Media, Finance, and Life Sciences. This diverse experience has cultivated a broad perspective on applying AI and Semantic Web principles. Influenced by Sir Tim Berners-Lee's concept of linked data and data sharing, Dean Allemang's work reflects a consistent focus on these principles. His contributions have advanced the field of AI and his current interest lies in how knowledge graphs can make generative AI more effective. Connect with Dean online LinkedIn Medium Resources mentioned in this interview Semantic Web for the Working Ontologist A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databases, Juan Sequeda, Dean Allemang, Bryon Jacob The Semantic Web, Tim Berners-Lee, James Hendler, and Ora Lassila Video Here’s the video version of our conversation: https://youtu.be/29kmAc6tobU Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 6. Long before the introduction of the semantic web - the innovation that added meaning and metadata to documents on the web - AI pioneers like Dean Allemang had been thinking about how knowledge could be formalized to help people do their work. The web itself, along with the W3C standards that power its semantic capabilities, gave Dean and his peers the ability to scale and connect existing practices and technologies to build a more meaningful web. Interview transcript Larry: Things. Hi everyone. Welcome to episode number six of the Knowledge Graph Insights podcast. I am really delighted today to welcome to the show, Dean Allemang. Dean is a principal solutions architect at data.world, a company in this space. He's also the author of The Semantic Web for the Working Ontologist, kind of the original operating manual and textbook for this field. So welcome, Dean. Tell the folks a little bit more about what you're up to these days. Dean: Hi, Larry. It's great to be here. So I've been at data.world for about three years now. I was an independent consultant for a bit before that. What I have been up to lately, not surprisingly, is figuring out how all of the new AI fits in with the sort of knowledge-intensive stuff that we've been doing with ontologies and knowledge graphs and things like that. Larry: Cool. Yeah, and I'd love to talk more about that research, time permitting, but I'll certainly link to it. I know you have a lot of cool new stuff coming up too, so I'll be sure to keep it. I'll try to keep the web page updated too with that. Larry: But hey, I want to back up just a little bit, like the dawn of this technology and this whole ecosystem we're operating in the semantic web. That's the first two words in your title of your book. Tell us folks a little bit more about the semantic web, its origins, what it is. Dean: Yeah, so one of the things I like to say about the semantic web is that the emphasis is on the final syllable; it's about web. That's the important insight that the semantic web brings to. Well, at the time, knowledge representation was the big thing, and the real key to the semantic web is in fact the web nature of it. So what you're doing in the semantic web, and this is a vision that came from Tim Berners-Lee in the mid, that sort of got more popular in the late 90s when the standards started to come through. But the idea is that we have this notion of the web; cast your mind back to the nineties when the web was a new thing, and instead of just having pages linking off to each other, could you actually have bits of knowledge that refer to each other in a deep, meaningful, dare I say it, semantic way. Dean: So Tim Berners-Lee came up with the name semantic web, and the point of it was that we want to be sharing not just documents on the web but meaning on the web. And that was the whole idea from Tim Berners-Lee, basically in the 90s. In some sense, he often says that this is the web he always had in mind, but the document web that we know and love was the first, the crawl of the crawl walk, run of the semantic web. That's how Tim often refers to it. But for us, this is really looking at knowledge representation, which has been around for a long time, and bringing it forward to the new information age, which is what we now call the web. Larry: Yeah, and one thing I want to point out is that one of the co-authors of your book is James Hendler, who famously co-wrote the paper with Tim Berners-Lee about introducing the idea that of... Dean: That's right. The Scientific American article back in 2001, I think it was? Larry: I think it was March or May; it was one of those M months in 2001. Yes. Dean: Yeah, early in '01. And that really sort of put the name on the idea of the semantic web. And so that was sort of how it all began, and the point of my book, which, as Jim and I wrote the first edition, I guess about seven years later, we were doing a course, a little corporate training with our partners, TopQuadrant, at the time, about semantic web. And we found that after four days of intense lectures and exercises and things, that we still found that a lot of very smart people were pretty tentative about answering basic questions about the semantic web. Well, we really need something to give them at the end of this course that they can take home and read. And so, one day over a beer, after doing this course, Jim and I conceived the idea of semantic web for the Working Ontologist and started to work on it. And of course, as I know you're aware, Larry, projects like this always take much longer than you expect. And I think it was actually three years later that we finally had the manuscript ready for the publisher. Larry: I don't know what you're talking about. When I was a book editor, everything that always came in early and no... I know how it goes, but hey, I want to talk... I love the origin story because it comes right out of what you want this book to be doing. It's like, "Okay, these people who are learning..." Because there's new technology, well, there's kind of two things. I guess you mentioned that knowledge representation has been around as a discipline for a while and then, but I'm going to guess it wasn't as technical as it is now or the specific technical implementation of it changed with the advent of the semantic web. Dean: Yes, that's certainly the case. Well, back in the really old days, things like what KL-ONE was a lisp-based knowledge, representation, language, and loom and all these things. They were actually very technical, indeed. What they weren't was distributed. That's why I say the emphasis on the final word web, and this is the thing that actually, if there's one thing about the semantic web that I find doesn't get through is that what we're doing here is sharing knowledge. So if you think about the EDM Council, one of my former clients, they published an ontology called FIBO, the Financial Industry Business Ontology. What are they doing there? They're writing down a data model. Well, anybody could write a data model, a lots of people do, and they are publishing it, and people do that as well. The OMG does a lot of that stuff. But why did the EDM Council decide to use the semantic web? Dean: They want people to be able to refer to parts of that independent of some document. They want to have a machine-readable way of bringing this into their system so that every last part of this great, big behemoth can be referenced on its own.