We present a novel semantic framework for modeling linguistic expressions of\ngeneralization---generic, habitual, and episodic statements---as combinations\nof simple, real-valued referential properties of predicates and their\narguments. We use this framework to construct a dataset covering the entirety\nof the Universal Dependencies English Web Treebank. We use this dataset to\nprobe the efficacy of type-level and token-level information---including\nhand-engineered features and static (GloVe) and contextual (ELMo) word\nembeddings---for predicting expressions of generalization. Data and code are\navailable at decomp.io.\n