Hi, I am using Rasa Open Source version 3.6.16. Trying to enhance entity recognition. I have a problem where entities that are not in the NLU examples will not be recognized, or they will be confused with another entity although the examples are different. (for example, if a company name: deal_with is not in the training data then depending on pipeline it will not extract it or confuse it with deal_name) Can anyone help with methods to better extract the entities please ? I am not very familiar with NLU so any advice will be helpful. Thank you. NLU: - intent: deal_with examples: | - [Deal]{"entity": "deal", "value": "Yes"} will be with [Google]{"entity": "deal_with"}. - [planning a deal]{"entity": "deal", "value": "Yes"} with [Microsoft]{"entity": "deal_with"} platform. - making a [deal]{"entity": "deal", "value": "Yes"} with [Twitter]{"entity": "deal_with"}. - the [deal]{"entity": "deal", "value": "Yes"} is with [linkedin]{"entity": "deal_with"} - the [deal]{"entity": "deal", "value": "Yes"} is to be with [Facebook]{"entity": "deal_with"} - intent: deal_name examples: | - The [deal]{"entity": "deal", "value": "Yes"} name will be [name]{"entity": "deal_name"}. - Consider [name]{"entity": "deal_name"} as the name for our [deal]{"entity": "deal", "value": "Yes"}. - The name of the [deal]{"entity": "deal", "value": "Yes"} will be [name]{"entity": "deal_name"} - We'll give the name [name]{"entity": "deal_name"} for the [deal]{"entity": "deal", "value": "Yes"} access. pipeline: - name: "SpacyNLP" model: "en_core_web_md" # case_sensitive: False - name: "SpacyTokenizer" - name: "SpacyFeaturizer" "pooling": "mean" # or max - name: RegexFeaturizer - name: CountVectorsFeaturizer analyzer: char_wb min_ngram: 1 max_ngram: 4 - name: "CRFEntityExtractor" # - name: "SpacyEntityExtractor" # dimensions to extract # dimensions: ["PERSON", "LOC", "ORG", "PRODUCT"] - name: DIETClassifier epochs: 100 constrain_similarities: true - name: EntitySynonymMapper - name: ResponseSelector epochs: 100 constrain_similarities: true - name: FallbackClassifier threshold: 0.3 ambiguity_threshold: 0.1

NLU and pipeline for entities

stephens (Greg Stephens) March 30, 2024, 2:34am 2

There’s a good blog post on entity extraction here

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