Description: " our work presents
the first approach that eliminates the need for
word-level negation labels, replacing it instead with document-level sentiment annotations. For this, we present a novel strategy
for learning fully interpretable negation rules
via weak supervision: we apply reinforcement
learning to find a policy that reconstructs negation rules from sentiment predictions at document level."