The MegaAcceptability dataset

Authors: Aaron Steven White and Kyle Rawlins

Contact: aaron.white@rochester.edu, kgr@jhu.edu

Version: 1.1

Release date: 14 Aug 2019

Overview

This MegaAcceptability dataset consists of ordinal acceptability judgments for 1,000 clause-embedding verbs of English in 50 surface-syntactic frames. The data were collected on Amazon’s Mechanical Turk using Turktools.

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.

Version history

1.0: first public release, 30 Oct 2016 1.1: formatting update, 14 Aug 2019

Description

Column Description Values
participant anonymous integer identifier for participant that provided the response 0…728
list integer identifier for list participant was responding to 0…999
presentationorder relative position of item in list 1…50
verb clause-embedding verb found in the item see paper
frame clausal complement found in the item see paper
response ordinal scale acceptability response 1…7
nativeenglish whether the participant reported speaking American English natively True, False
sentence sentence that was judged see paper

Notes

• Only participants for which exclude==True are included in the analysis in White & Rawlins 2016. The full exclusion procedure is laid out in a paper in preparation.
• A javascript error produced 10 NA values for response, none of which affect the same verb-frame pair.