Distilling Text into Circuits
Vincent Wang-Mascianica, Jonathon Liu, Bob Coecke

TL;DR
This paper develops DisCoCirc, a framework that creates language-independent, compositional text circuits capturing the core meanings of text, applicable across languages and modalities, and demonstrates its realization for a fragment of English.
Contribution
It introduces a hybrid grammar and translation process to generate and interpret text circuits, advancing the understanding of universal meaning structures beyond language-specific syntax.
Findings
DisCoCirc applies to a substantial fragment of English.
Text circuits are language-independent and universal.
The framework is generative for text.
Abstract
This paper concerns the structure of meanings within natural language. Earlier, a framework named DisCoCirc was sketched that (1) is compositional and distributional (a.k.a. vectorial); (2) applies to general text; (3) captures linguistic `connections' between meanings (cf. grammar) (4) updates word meanings as text progresses; (5) structures sentence types; (6) accommodates ambiguity. Here, we realise DisCoCirc for a substantial fragment of English. When passing to DisCoCirc's text circuits, some `grammatical bureaucracy' is eliminated, that is, DisCoCirc displays a significant degree of (7) inter- and intra-language independence. That is, e.g., independence from word-order conventions that differ across languages, and independence from choices like many short sentences vs. few long sentences. This inter-language independence means our text circuits should carry over to other…
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Taxonomy
TopicsNatural Language Processing Techniques · Language and cultural evolution · Speech and dialogue systems
