I’m pretty new to Rasa and was exploring its capabilities when a strange behavior occurred. I had started by creating a nlu model capable of intent classification and entity extraction for my native language, which worked fine when made available through http.
Example:
Request: { “q”:“Procuro um restaurante italiano em 12345” }
Response: { “intent”: { “name”: “restaurant_search”, “confidence”: 0.7113155505293147 }, “entities”: [{ “entity”: “cuisine”, “value”: “italiano”, “start”: 23, “end”: 31, “confidence”: null, “extractor”: “ner_mitie” }, { “entity”: “location”, “value”: “12345”, “start”: 35, “end”: 40, “confidence”: null, “extractor”: “ner_mitie” }], “intent_ranking”: [{ “name”: “restaurant_search”, “confidence”: 0.7113155505293147 }, { “name”: “greet”, “confidence”: 0.15049657601423475 }, { “name”: “affirm”, “confidence”: 0.0821662299874645 }, { “name”: “goodbye”, “confidence”: 0.0560216434689861 }], “text”: “Procuro um restaurante italiano em 12345”, “project”: “default”, “model”: “model_20181210-181406” }
However, when I used the model through a Rasa_core bot something unexpected happened with the model. Everything works fine while no entities are present in a message, however, whenever an entity is present no intent is detected. As an example something like: “Procuro restaurante” - Looking for a restaurant Works While: “Procuro restaurante mexicano” - Looking for a mexican restaurant Doesn’t
Relevant information:
Rasa Core version : 0.12.3
Python version : 3.6
Operating system (windows, osx, …): ubuntu 18.04
Content of domain file (if used & relevant):
language: "pt"
pipeline:
- name: "nlp_mitie"
model: "data/total_word_feature_extractor_pt.dat"
- name: "tokenizer_mitie"
- name: "ner_mitie"
- name: "ner_synonyms"
- name: "intent_entity_featurizer_regex"
- name: "intent_featurizer_mitie"
- name: "intent_classifier_sklearn"
Edit: This is the training data used demo-rasa-pt.json (5.1 KB)
Any help regarding this issue would be greatly appreciated.
