ACL 2016Short
Annotating Relation Inference in Context via Question Answering
作者: Omer Levy, Ido Dagan
摘要
We present a new annotation method for collecting data on relation inference in context. We convert the inference task to one of simple factoid question answering, allowing us to easily scale up to 16,000 high-quality examples. Our method corrects a major bias in previous evaluations, making our dataset much more realistic.