  Document-level Relation Extraction (RE) is a more challenging task than
sentence RE as it often requires reasoning over multiple sentences. Yet, human
annotators usually use a small number of sentences to identify the relationship
between a given entity pair. In this paper, we present an embarrassingly simple
but effective method to heuristically select evidence sentences for
document-level RE, which can be easily combined with BiLSTM to achieve good
performance on benchmark datasets, even better than fancy graph neural network
based methods. We have released our code at
https://github.com/AndrewZhe/Three-Sentences-Are-All-You-Need.
