  A challenging case in web search and question answering are count queries,
such as \textit{"number of songs by John Lennon"}. Prior methods merely answer
these with a single, and sometimes puzzling number or return a ranked list of
text snippets with different numbers. This paper proposes a methodology for
answering count queries with inference, contextualization and explanatory
evidence. Unlike previous systems, our method infers final answers from
multiple observations, supports semantic qualifiers for the counts, and
provides evidence by enumerating representative instances. Experiments with a
wide variety of queries show the benefits of our method. To promote further
research on this underexplored topic, we release an annotated dataset of 5k
queries with 200k relevant text spans.
