It seems that the the ML/NLP steps described in scenario three are substantially similar to those described by the EUCJ in the reported case law.
: 1. transforming the text corpus and the annotations into the input format of the Stanford NER tool is arguably equivalent to converting a TIFF image into text using OCR but much less sophisticated; 2. inspecting each word in the text in turn in order to create a ML feature representation capturing from the word and its immediate left and right neighbours, and from the annotation on the word is arguably equivalent to extracting the search term and the words before and after it, although extracting only one word before/after instead of 5, for a total of 3 words instead of 11 words extracted; 3. creating a probabilistic report (i.e.