Towards Evaluating Plan Generation Approaches with Instructional Texts
  Recent research in behaviour understanding through language grounding has
shown it is possible to automatically generate behaviour models from textual
instructions. These models usually have goal-oriented structure and are
modelled with different formalisms from the planning domain such as the
Planning Domain Definition Language. One major problem that still remains is
that there are no benchmark datasets for comparing the different model
generation approaches, as each approach is usually evaluated on domain-specific
application. To allow the objective comparison of different methods for model
generation from textual instructions, in this report we introduce a dataset
consisting of 83 textual instructions in English language, their refinement in
a more structured form as well as manually developed plans for each of the
instructions. The dataset is publicly available to the community.
