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

Venkata Govindarajan, Benjamin Van Durme, Aaron Steven White


Abstract
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 static (GloVe) and contextual (ELMo) word embeddings—for predicting expressions of generalization.
Anthology ID:
Q19-1035
Volume:
Transactions of the Association for Computational Linguistics, Volume 7
Month:
Year:
2019
Address:
Cambridge, MA
Editors:
Lillian Lee, Mark Johnson, Brian Roark, Ani Nenkova
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
501–517
Language:
URL:
https://aclanthology.org/Q19-1035
DOI:
10.1162/tacl_a_00285
Bibkey:
Cite (ACL):
Venkata Govindarajan, Benjamin Van Durme, and Aaron Steven White. 2019. Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements. Transactions of the Association for Computational Linguistics, 7:501–517.
Cite (Informal):
Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements (Govindarajan et al., TACL 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-5/Q19-1035.pdf
Data
ECB+English Web TreebankFrameNet