  In this paper, we introduce LiveQA, a new question answering dataset
constructed from play-by-play live broadcast. It contains 117k multiple-choice
questions written by human commentators for over 1,670 NBA games, which are
collected from the Chinese Hupu (https://nba.hupu.com/games) website. Derived
from the characteristics of sports games, LiveQA can potentially test the
reasoning ability across timeline-based live broadcasts, which is challenging
compared to the existing datasets. In LiveQA, the questions require
understanding the timeline, tracking events or doing mathematical computations.
Our preliminary experiments show that the dataset introduces a challenging
problem for question answering models, and a strong baseline model only
achieves the accuracy of 53.1\% and cannot beat the dominant option rule. We
release the code and data of this paper for future research.
