Find Answers in Tables with TAPAS

Quite intriguing, a very common kind of sub problem for interacting with data.  Good descriptive technical piece.  Released.    Worth a look. 

Using Neural Networks to Find Answers in Tables
Posted by Thomas Müller, Software Engineer, Google Research  in Google AI. 

Much of the world’s information is stored in the form of tables, which can be found on the web or in databases and documents. These might include anything from technical specifications of consumer products to financial and country development statistics, sports results and much more. Currently, one needs to manually look at these tables to find the answer to a question or rely on a service that gives answers to specific questions (e.g., about sports results). This information would be much more accessible and useful if it could be queried through natural language.

For example, the following figure shows a table with a number of questions that people might want to ask. The answer to these questions might be found in one, or multiple, cells in a table (“Which wrestler had the most number of reigns?”), or might require aggregating multiple table cells (“How many world champions are there with only one reign?”). ... "