NER: all confidences per Token with DIETClassifier

[Novaal]

Description of Problem: Thanks for introducing the confidences for NER with #6038. Currently only the labels for the best matching entity is given. I would like to have an option to get all confidences including the confidences for labels with NO_ENTITY_TAG on a per token basis. This would allow me for example to choose the second best entity for specific tokens.

Overview of the Solution:

Change _predict_entities() to return a list of confidences on a per Token basis.

Examples (if relevant):

• _predict_entities()
• [ convert_predictions_into_entities()|

  rasa/rasa/nlu/extractors/extractor.py

  Line 131 in 2e7f49f

  def convert_predictions_into_entities(

  ]

It could be an similar aproach like in _predict_label()

[sara-tagger]

Exalate commented:

sara-tagger commented:

Thanks for submitting this feature request

🚀
@erohmensing will get back to you about it soon!

✨

[Novaal]

Exalate commented:

Novaal commented:

It seems to be, that _predict_entities() is also inconsistent to _predict_label() in the way, that if i have multiple classifiers for intents+entities, the last classifier will overwrite the intents and intent_rankings, but will add the entities to the list of the previous classifiers. Then its not necessarily distinguishable anymore, which classifier provided, which entity.

rasa/rasa/nlu/classifiers/diet_classifier.py

Line 859 in 9690842

entities = message.get(ENTITIES, []) + entities

[stale]

Exalate commented:

stale[bot] commented:

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

[sync-by-unito]

➤ Maxime Verger commented:

💡 Heads up! We're moving issues to Jira: https://rasa-open-source.atlassian.net/browse/OSS.

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