  We release a corpus of 43 million atomic edits across 8 languages. These
edits are mined from Wikipedia edit history and consist of instances in which a
human editor has inserted a single contiguous phrase into, or deleted a single
contiguous phrase from, an existing sentence. We use the collected data to show
that the language generated during editing differs from the language that we
observe in standard corpora, and that models trained on edits encode different
aspects of semantics and discourse than models trained on raw, unstructured
text. We release the full corpus as a resource to aid ongoing research in
semantics, discourse, and representation learning.
