Revolutionary entities: Turning data into knowledge to drive personalized exploration of The irish rising of 1916

`Big Data´ can mean something quite different in the context of Humanities. The way Humanities scholars frame their inquiries often leverages collections that are an order of magnitude smaller than the full, industrial scale, there is significant value to be found in the Humanistic sense of `Big´. In particular, the variety of the data, and the richness of the explorations, means that high-quality knowledge systems are required. More meaning is needed than the surface analytics often demonstrated in other `Big´ scenarios. This paper examines how a specific collection related to the 1916 Rising in Ireland was analyzed. The result was a process to extract entities that underpinned a highly-effective personalized knowledge-driven exploration of that collection by users. It demonstrates the mutual benefit of natural language at scale with rich humanistic inquiry to communicate improved experiences for a much broader range of users than would otherwise be possible.