I am using ner_crf in my pipeline. When I run the code in evaluate.py to get my performance statistics, I get summary results for both intents and entities. Not only this, if I include the successes command line argument I get both predicted and expected intent values (with confidences). Unfortunately, I cannot find how to get the same predicted/expected pairs with entities. F-Scores are great in proving that I am doing well overall, but I need to check out my misses. Is there an easy way to access to those entities that I am not predicting correctly (both FP and FN really).
Hi there @grjasewe,
Unfortunately there is currently only the implementation of
errors.json (shows unmatched expected/predictions) for intent classification, not entity extraction. This is however a feature request that we’re aware of and are considering implementing when we get the chance. Sorry that there is no easy solution at the moment!
Disappointed, but thanks. Do you have a link to the feature request so that I may follow its progress?