122 - Statutory Reasoning in Tax Law, with Nils Holzenberger

We invited Nils Holzenberger, a PhD student at JHU to talk about a
dataset involving statutory reasoning in tax law Holzenberger et
al. released recently. This dataset includes difficult textual
entailment and question answering problems that involve reasoning
about how sections in tax law are applicable to specific cases.
They also released a Prolog solver that fully solves the problems,
and show that learned models using dense representations of text
perform poorly. We discussed why this is the case, and how one can
train models to solve these challenges. Project webpage:
https://nlp.jhu.edu/law/