ManyNames gathers many more names per object than previous datasets: 35.3 on average. It also contains the most variability, since objects have on average 5.7 names. ManyNames shows high potential use for studying the degree of inter-subject naming agreement, and what factors influence variation.

Despite the care in filtering out objects that are occluded or have unclear bounding boxes, there are still many examples where annotators identified different objects for the same box. Typically, workers named an adjacent object or one supported by the target object, or a part of the target object. While some of these cases are arguably annotation errors, in many cases it is not possible to distinguish which object is being indicated by the box. Referential uncertainty of this kind is a roadblock for the use of L&V resources to study naming variation.