Navigating the Interplay Between Human Thought and Language Models

Emeka Okoye Semantic technologies permit powerful connections across a variety of linked data resources across the web. Until recently, developers had to learn the RDF language to discover and use these resources. Leveraging the new Model Context Protocol (MCP) and LLM-powered natural-language interfaces, Emeka Okoye has created the RDF Explorer, an MCP service that lets any developer surf the semantic web without having to learn its specialized language. We talked about: his long history in knowledge engineering and AI agents his deep involvement in the business and technology communities in Nigeria, including founding the country's first internet startup how he was building knowledge graphs before Google coined the term an overview of MCP, the Model Context Protocol, and its benefits the RDF Explorer MCP server he has developed how the MCP protocol and helps ease some of the challenges that semantic web developers have traditionally faced the capabilities of his RDF Explorer: facilitating communication between AI applications, language models, and RDF data enabling graph exploration and graph data analysis via SPARQL queries browsing, accessing, and evaluating linked-open-data RDF resources the origins of RDF Explorer in his attempt to improve ontology engineering tooling his objections to "vibe ontology" creation the ability of RDF Explorer to let non-RDF developers users access knowledge graph data how accessing knowledge graph data addresses the problem of the static nature of the data in language models the natural connections he sees between neural network AI and symbolic AI like knowledge graphs, and the tech tribalism he sees in the broader AI world that prevents others from seeing them how the ability of LLMs to predict likely language isn't true intelligence or actual knowledge some of the lessons he learned by building the RDF Explorer, e.g., how the MCP protocol removes a lot of the complexity in building hybrid AI solutions how MCP helps him validate the ontologies he creates Emeka's bio Emeka is a Knowledge Engineer, Semantic Architect, and Generative AI Engineer who leverages his over two decades of expertise in ontology and knowledge engineering and software development to architect, develop, and deploy innovative, data-centric AI products and intelligent cognitive systems to enable organizations in their Digital Transformation journey to enhance their data infrastructure, harness their data assets for high-level cognitive tasks and decision-making processes, and drive innovation and efficiency enroute to achieving their organizational goals. Emeka’s experience has embraced a breadth of technologies his primary focus being solution design, engineering and product development while working with a cross section of professionals across various cultures in Africa and Europe in solving problems at a complex level. Emeka can understand and explain technologies from deep diving under the hood to the value proposition level. Connect with Emeka online LinkedIn Making Knowledge Graphs Accessible: My Journey with MCP and RDF Explorer RDF Explorer (GitHub) Video Here’s the video version of our conversation: https://youtu.be/GK4cqtgYRfA Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 36. The widespread adoption of semantic technologies has created a variety of linked data resources on the web. Until recently, you had to learn semantic tools to access that data. The arrival of LLMs, with their conversational interfaces and ability to translate natural language into knowledge graph queries, combined with the new Model Context Protocol, has empowered semantic web experts like Emeka Okoye to build tools that let any developer surf the semantic web. Interview transcript Larry: Hi, everyone. Welcome to episode number 36 of the Knowledge Graph Insights podcast.