Natural Language Understanding for MapTask

About a decade ago, University of Edinburgh and its partners put together a collection of transcribed human/human dialogues in which both participants were given similar maps. The person giving instructions had to navigate the other particpant along a path only on the giver's map. Since then, this corpus has been used for various tasks. To our knowledge, there have been no attempts to model actual understanding on the instruction receiver end; this study aims to fill this gap. We introduce Navigational Information Units (NIUs) describing individual intervals of the paths, drawn from several categories (such as "moves" and "positions"). Our first aim is to decompose these NIUs into a number of possibly independent constituents and ground the latter in terms of the objects on the maps. Having such models at hand, we can further employ the notion of context and try and replicate the entire paths as a sequence of extracted NIUs.