Bethard and Parker (2016) proposed an alternate scheme, Semantically Compositional Annotation of Time Expressions (SCATE), in which times are annotated as compositional time entities (Figure 1), and suggested that this should be more amenable to machine learning.
while they constructed an annotated corpus, they did not train any automatic models on it.