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Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements

Publication

Abstract

We present a novel semantic framework for modeling linguistic expressions ofgeneralization— generic, habitual, and episodic statements—as combinations of simple,real-valued referential properties of predicates and their arguments. We usethis framework to construct a dataset covering the entirety of the Universal

Dependencies English Web Treebank. We use this dataset to probe the efficacy oftype-level and token-level information—including hand-engineered featuresand static (GloVe) and contextual (ELMo) word embeddings—for predictingexpressions of generalization.