Trainability and real-world knowledge
András Kornai · Cognitive technologies · 2022
Until this point, we concentrated on the lexicon, conceived of as the repository of shared linguistic information. In 8.1 we take on the problem of integrating real-world knowledge, nowadays typically stored in knowledge graphs as billions of RDF triples, and linguistic knowledge, stored in a much smaller dictionary, typically compressible to a few megabytes. We present proper names as point vectors (rather than the polytopes we use for common nouns and most other lexical entries), and introduce the notion of content continuations, algorithms that extend the lexical entries to more detailed hypergraphs that can refer to technical nodes, such as Date, FloatingPointNumber, or Obligation (see 9.1) that are missing from the core lexicon.