WikiAtomicEdits: A Multilingual Corpus of Wikipedia Edits for Modeling Language and Discourse
This provides a resource for researchers in semantics, discourse, and representation learning, but it is incremental as it builds on existing edit mining approaches.
The authors tackled the problem of modeling language and discourse by releasing a corpus of 43 million atomic edits from Wikipedia across 8 languages, showing that edit-generated language differs from standard corpora and trains models to encode distinct semantic and discourse aspects.
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.