{"url":"/dataset/megaacceptability","name":"MegaAcceptability","full_name":null,"description_markdown":"The MegaAcceptability dataset is a collection of ordinal acceptability judgments for clause-embedding verbs of English in various surface-syntactic frames and matrix tenses. Here are some key details:\r\n- It includes judgments for **1,007 clause-embedding verbs** of English in **50 surface-syntactic frames** and **three matrix tenses**.\r\n- The dataset combines the MegaAcceptability version 1.0 and data collected for **25,000 additional verb-frame pairs** on Amazon’s Mechanical Turk using Ibex on Mechanical Turk.\r\n- The dataset has been used to address questions in linguistic theory.","description_withheld":null,"homepage":"http://megaattitude.io/projects/mega-acceptability/","introduced_date":"2019-08-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-lexical-and-grammatical-sources-of-neg","title":"The lexical and grammatical sources of neg-raising inferences","first_author":"Hannah Youngeun An","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["MegaAcceptability"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}