We evaluate the performance of SeNsER with regard to chunking and tagging using the precision, recall, and F 1 scores, similar to NER tasks.
for each sensor name, we get a few predicted triplets, i.e., (position begin , position end , category), and only when both the position and category exactly match the ground-truth annotations does it count as a correct extraction.