SQuAD: 100,000+ Questions for Machine Comprehension of Text

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We present the Stanford Question Answering Dataset (SQuAD), a new reading comprehension dataset consisting of 100,000+ questions posed by crowdworkers on a set of Wikipedia articles, where the answer to each question is a segment of text from the corresponding reading passage.

• We analyze the dataset to understand the types of reasoning required to answer the questions, leaning heavily on dependency and constituency trees.
• We build a strong logistic regression model, which achieves an F1 score of 51.0%, a significant improvement over a simple baseline (20%).
• However, human performance (86.8%) is much higher, indicating that the dataset presents a good challenge problem for future research.