  Open Information Extraction (OIE) systems seek to compress the factual
propositions of a sentence into a series of n-ary tuples. These tuples are
useful for downstream tasks in natural language processing like knowledge base
creation, textual entailment, and natural language understanding. However,
current OIE datasets are limited in both size and diversity. We introduce a new
dataset by converting the QA-SRL 2.0 dataset to a large-scale OIE dataset
(LSOIE). Our LSOIE dataset is 20 times larger than the next largest
human-annotated OIE dataset. We construct and evaluate several benchmark OIE
models on LSOIE, providing baselines for future improvements on the task. Our
LSOIE data, models, and code are made publicly available
