Comonadic Morphophonology: A Compositional Framework for Context-Dependent Morphological Rules in Finnish
Not on the map. Why?
Abstract (arXiv)
Composing finite-state transducers (FSTs) for context-dependent morphophonological rules -- consonant gradation, vowel harmony, possessive suffix assimilation -- leads to multiplicative state explosion; neural models sidestep the problem but provide no formal account of the rules themselves. We present the first framework where each morphophonological rule is a function from a focused local context to a single output segment -- the type of a local rule familiar from cellular automata -- and where length-changing rules compose as coKleisli arrows of a comonad. Our central contribution is the Writer comonad (DeletionSet x Zipper), a new algebraic construction that restores strict coKleisli compositionality for such rules: each rule is a coKleisli arrow, extend lifts it to a global transformation, and deletions accumulate as a monoid action rather than requiring intermediate materialization. As supporting evidence, thirteen coKleisli arrows provide an alternative formulation expressing the same morphophonological behaviors that Omorfi encodes via 874 continuation classes (67:1 reduction at the rule-representation level), and the same abstraction enables bidirectional morphology -- a MorphGenerator reuses the analysis arrows for generation. On UD Finnish-TDT, the system achieves 83.92% UPOS accuracy with rule-only disambiguation (94.66% with an external suffix tagger), validating the framework as a practical morphological engine.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 28 references that are in the map. First posted on arXiv 27 May 2026.
Builds on
4 of 28 references.
References · 4
- 2021Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processingcited by 68
- 2022The SIGMORPHON 2022 Shared Task on Morpheme Segmentationcited by 25
- 2022Categorical Tools for Natural Language Processingcited by 3
- 2024Recent advancements in computational morphology : A comprehensive surveycited by 2
Built on by
Not cited yet.