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Effect-driven interpretation: Functors for natural language composition

Published: April 1, 2025 | arXiv ID: 2504.00316v1

By: Dylan Bumford, Simon Charlow

Potential Business Impact:

Makes computer programs understand language like humans.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Computer programs are often factored into pure components -- simple, total functions from inputs to outputs -- and components that may have side effects -- errors, changes to memory, parallel threads, abortion of the current loop, etc. We make the case that human languages are similarly organized around the give and pull of pure values and impure processes, and we'll aim to show how denotational techniques from computer science can be leveraged to support elegant and illuminating analyses of natural language composition.

Page Count
149 pages

Category
Computer Science:
Computation and Language