2022 NAACL NAACL 2022

Simulating Feature Structures with Simple Types

Abstract

AbstractFeature structures have been several times considered to enrich categorial grammars in order to build fine-grained grammars. Most attempts to unify both frameworks either model categorial types as feature structures or add feature structures on top of categorial types. We pursue a different approach: using feature structure as categorial atomic types. In this article, we present a procedure to create, from a simplified HPSG grammar, an equivalent abstract categorial grammar (ACG). We represent a feature structure by the enumeration of its totally well-typed upper bounds, so that unification can be simulated as intersection. We implement this idea as a meta-ACG preprocessor.

🌉 Interdisciplinary Bridge — Computer Science and Interdisciplinary
🧭 Keyword Pioneer — abstract categorial grammar
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics