Session 7
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For most of recorded history, logic was seen as an attempt to systematize the entailment patterns observed in natural---that is to say, human---languages. Only with the rise of quantification theory and the emergence of mathematical logic at the end of the nineteenth century did the syntactic structure of natural language lose its pre-eminence. Recently, however, there has been a resurgence of interest in natural language reasoning, as a result of two very different developments. ...
Vector representations of words are commonly used to give language models a basic understanding of a domain’s vocabulary, and various techniques have been developed to build good such representations from a text corpus, a knowledge graph, or an ontology. In this talk, I will talk about such representations and what it means for a such a representation to faithfully represent the relationships between concepts, individuals, and relations from an ontology. In part...
We defend best practices for the field of ontology engineering in support of simultaneously addressing interoperability and data quality challenges through a standardized tradecraft. Ontology engineering requires precisely making explicit the implicit semantics of data, but in practice ontology engineers frequently defer too much to domain experts, commonsense intuitions, and labeling conventions, while avoiding the modeling complexity that interoperability requ...
Large Language Models (LLMs) are well known for their remarkably fluent natural-language interaction with information systems, but their outputs are not, by themselves, trustworthy: they lack governance, provenance, auditability, and accountability. In this session, I explore an alternative architectural role for LLMs—not as autonomous answer generators, but as semantic interfaces to curated and governed data resources.I begin ...