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

We present a novel semantic framework for modeling linguistic expressions of generalization - generic, habitual, and episodic statements - as combinations of simple, real-valued referential properties of predicates and their arguments. We use this framework to construct a dataset covering the entirety of the Universal Dependencies English Web Treebank. We use this dataset to probe the efficacy of type-level and token-level information - including hand-engineered features and contextual and non-contextual word embeddings - for predicting expressions of generalization. Data and code are available at decomp.io.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro