Since the Automatic Content Extraction program in 2004 there has been a separate task identified and called Temporal Expression Recognition and Normalisation (TERN).
[1] Similarly to NER systems, temporal expression taggers have been created either using linguistic grammar-based techniques or statistical models.
Hand-crafted grammar-based systems typically obtained better results, but at the cost of months of work by experienced linguists.
There are many such systems available now,[2][3][4] so creating a temporal expression recognizer from scratch is generally an undesirable duplication of effort.
[5] Statistical systems typically require a large amount of manually annotated training data and are usually applied to the recognition task only (although there is work done using machine learning algorithms to resolve certain ambiguities in the interpretation step).