I updated from RASA 1.10.2 to 1.10.14. My pipeline is -: language: en pipeline: - name: SpacyNLP model: en_core_web_md - name: ConveRTTokenizer - name: ConveRTFeaturizer - name: RegexFeaturizer - name: LexicalSyntacticFeaturizer - name: CRFEntityExtractor - name: DIETClassifier epochs: 50 - name: EntitySynonymMapper - name: ResponseSelector epochs: 100 - name: SpacyEntityExtractor - name: "DucklingHTTPExtractor" url: "http://0.0.0.0:8000" locale: "en_GB" timezone: "US/Pacific" timeout : 3 In RASA 1.10.2 CRFEntityExtractor was working fine but in 1.10.14 it is splitting the entity into multiple tokens. Pls help If more information for nlu data is required will provide. Thanks!

I think there’s an issue by using spacy together with convert. They each come with their own tokenizer and I can imagine that they’re not playing nice with eachother. I also wonder, is there a particular reason you’re using the spaCy entity extractor? Are there specific entities that are pretrained in en_core_web_md that you’re interested in?

CRFEntityExtractor or DIETClassifier splits one entity into multiple words

Rasa Open Source

UlisesVD (Ulises Vd) September 25, 2020, 5:52pm 3

check this post: Introducing DIET: state-of-the-art architecture that outperforms fine-tuning BERT and is 6X faster to train

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CRFEntityExtractor or DIETClassifier splits one entity into multiple words

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