Data

MegaAcceptability

This MegaAcceptability dataset consists of ordinal acceptability judgments for ~1000 clause-embedding verbs of English in 50 surface-syntactic frames. The data were collected on Amazon’s Mechanical Turk using Turktools.

Download v1 (.zip)

For a detailed description of the dataset, the item construction and collection methods, and discussion of how to use a dataset on this scale to address questions in linguistic theory, please see the following paper:

White, A. S. & K. Rawlins. 2016. A computational model of S-selection. In M. Moroney, C-R. Little, J. Collard & D. Burgdorf (eds.), Semantics and Linguistic Theory 26, 641-663. Ithaca, NY: CLC Publications.

If you make use of this dataset in a presentation or publication, we ask that you please cite this paper.

MegaVeridicality

This MegaVeridicality dataset consists of ordinal veridicality judgments as well as ordinal acceptability judgments for 517 clause-embedding verbs of English. The data were collected on Amazon’s Mechanical Turk using Turktools.

Download v2 (.zip)

For a detailed description of the dataset, the item construction and collection methods, and discussion of how to use a dataset on this scale to address questions in linguistic theory, please see the following paper:

White, A. S., R. Rudinger, K. Rawlins, & B. Van Durme. (2018). Lexicosyntactic Inference in Neural Models. To appear in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31-November 4, 2018.

White, A. S. & K. Rawlins. 2018. The role of veridicality and factivity in clause selection. To appear in the Proceedings of the 48th Meeting of the North East Linguistic Society.

If you make use of this dataset in a presentation or publication, we ask that you please cite these papers.