Complexity of Grammar Induction for Quantum Types
This addresses a computational complexity issue for researchers in formal semantics and computational linguistics, but it is incremental as it extends known results to specific categorical frameworks.
The paper tackles the problem of grammar induction in categorical models of meaning, showing that for type systems like pivotal and compact closed categories, the grammar induction problem is NP-complete.
Most categorical models of meaning use a functor from the syntactic category to the semantic category. When semantic information is available, the problem of grammar induction can therefore be defined as finding preimages of the semantic types under this forgetful functor, lifting the information flow from the semantic level to a valid reduction at the syntactic level. We study the complexity of grammar induction, and show that for a variety of type systems, including pivotal and compact closed categories, the grammar induction problem is NP-complete. Our approach could be extended to linguistic type systems such as autonomous or bi-closed categories.