Example :slight_smile: Failed cases : 1- it is a red 2- chf 3- rub 4- aziz 5- yellow intent:check_balance what is my balance Could I pay in yen ? USD intent:Greet How doing jack hello steve intent:ColorsIntent i like gray I am interested in white it is a black color ##intent:Bored I am bored it is boring it is bored lookup:currency Yen USD Euro PKR jpy chf cad mxn rub lookup:name aziz ron rehan sahal lookup:color red yellow orange language: “en” pipeline: name: “nlp_spacy” model: “en_core_web_md” case_sensitive: false name: “tokenizer_spacy” name: “intent_entity_featurizer_regex” name: “ner_duckling” dimensions: [“time”,“number”,“phone-number”,“email”] name: “ner_crf” features: features for word before token [“low”, “title”, “upper”] features of token itself [“bias”, “low”, “prefix5”, “prefix2”,“suffix5”, “suffix3”, “suffix2”,“digit”,“upper”, “title”, “pattern”] features for word after the token we want to tag [“low”, “title”, “upper”] max_iterations: 50 L1_c: 0.1 L2_c: 0.1 name: “ner_synonyms” name: “intent_featurizer_count_vectors” name: “intent_classifier_tensorflow_embedding”

You need to include few examples with the content from your lookup table for it to work. For example, as you have red, yellow, orange in your lookup, add these ##intent:ColorsIntent - i like red(color) - I am interested in yellow(color) - it is a black color(color)

There is no specific number. 3~4 examples from my lookup table works for me.

what if have different values of hundreds ? There is alot of variations ? There are not same length ? Somethinglike these ?? colors c3 ii c4 tour travato vectra via view and view view vista rialta adventure adventure cb500x cruiser cruiser 1300 custom line cruiser ctx700n cruiser fury cruiser goldwing f6b cruiser rebel cruiser shadow line dual sport dual sport crf250l super super cb1000r t@b trailblazer (lite) by komfort a.c.e. @akelad what do i have to do ? if have hurdreds of data kike this data ? bcz loopup data is not working, do I have to train on each of these ??

I’m not sure if it’ll work for such large variation, never tried it out. However, I guess your training data must include all such variations for it to work.

you have to include some examples of these entities in your training data

Hi all, do I have to give examples for all the existing entities in my lookup table? I am failing to understand, if i have to give all the entities in the training sets how is lookup table helpful?

Hi, I have very domain specific entities that are not well recognized in my model. So, I am trying to improve the accuracy of entity recognition by adding lookup tables. But I don’t see any improvement. Currently, I’m using DIET classifier and based on this post “ Entity lookup in DIET Classifier ” we can use lookup tables with DIET model as long as “RegexFeaturizer” is provided in the pipeline. I also added more training data with the same entity in my nlu data. But still I don’t see any changes. The other thing that I tried was adding “CRFEntityExtractor” which I’m not sure if it is a good idea or not, but still it didn’t help. Can you share your experience that what possibly could be the solution?

Having similar problems here - did anyone get a response to this?

Lookup table is not working

Rasa Open Source

prasanth55555 (Prasanth55555) July 8, 2019, 8:24am 8

@akelad @Juste @juste_petr can you please look into this issue Error while trying to create a look up table

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Lookup table is not working

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