Given the task definition and input, reply with output. In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

However, all previous IE benchmarks BIBREF18 are too small to train neural network models typically used in QA, and thus we need to build a large benchmark. Therefore, we build a large scale benchmark named QA4IE benchmark which consists of 293K Wikipedia articles and 2M golden relation triples with 636 different relation types. We manually find 148 relations which can be projected to a WikiData relation out of 2064 DBpedia relations.
Was this benchmark automatically created from an existing dataset?