  We describe two new related resources that facilitate modelling of general
knowledge reasoning in 4th grade science exams. The first is a collection of
curated facts in the form of tables, and the second is a large set of
crowd-sourced multiple-choice questions covering the facts in the tables.
Through the setup of the crowd-sourced annotation task we obtain implicit
alignment information between questions and tables. We envisage that the
resources will be useful not only to researchers working on question answering,
but also to people investigating a diverse range of other applications such as
information extraction, question parsing, answer type identification, and
lexical semantic modelling.
