  We introduce TechTrack, a new dataset for tracking entities in technical
procedures. The dataset, prepared by annotating open domain articles from
WikiHow, consists of 1351 procedures, e.g., "How to connect a printer",
identifies more than 1200 unique entities with an average of 4.7 entities per
procedure. We evaluate the performance of state-of-the-art models on the
entity-tracking task and find that they are well below the human annotation
performance. We describe how TechTrack can be used to take forward the research
on understanding procedures from temporal texts.
