Ctparse

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* Implemented new type `Duration`, to handle lengths of time
* Adapted the dataset to include `Duration`
* Implemented basic rule to merge `Duration`, `Time` and `Interval` in simple cases.
* Created a make target to train the model `make train`

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* Major refactor of code underlying predictive model
* Based on a contribution from bharathi-srini: replace naive bayes from sklearn by own implementation
* Thus remove dependencies on numpy, scipy, scikit-learn
* Predictions are much faster: 97/s in the old vs. 239/s in the new code base
* Performance identical
* Deprecate support for python 3.5, add 3.8
* Add more strict type checking rules (mypy.ini)
* Force black code formatting, make this a linter step, "black" all code

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* Allow overlapping matches of regular expression when generating inital stack of "tokens"

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* Implemented heuristics to detect (albeit imperfectly) military times

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* Released time corpus
* Implemented training model using ctparse corpus

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* Added slash as a general separator
* Added ruleTODTOD (to support expression like afternoon/evening)