Hi there!
I have some issues in using properly my lookuptables. Here’s the deal:
Even if I uploaded my lookup tables in /data folder

and added them in my nlu file

they are not being read by the NLU component. I added some examples in my training data coming from my lookup tables, but that simply didn’t work out.
I think that the trouble could be in the config.yml file, because I am using the pipeline supervised_embeddings. However, since my chatbot is in italian, i need that kind of pipeline. Moreover, if I try to add something in the pipeline, I simply get an error message when I train the model. Can somebody help?
Thx
Andrea
I came to the conclusion that you need to include CRFEntityExtractor
in the pipeline for it to work with lookup tables. For instance, DIETClassifier would ignore them. Maybe someone from @Rasa can shed some light.
Do I have to replace supervised_embeddings with `CRFEntityExtractor? This is how the config file looks like right now:

If I change it like this:

it fails the training because:

Sorry for late reply. I’m not exactly sure how CRFEntityExtractor
interacts with supervised_embeddings
. If it helps you, this is my config:
language: es_core_news_sm
pipeline:
- name: SpacyNLP
model: es_core_news_sm
- name: SpacyTokenizer
- name: SpacyFeaturizer
- name: RegexFeaturizer
- name: LexicalSyntacticFeaturizer
- name: CountVectorsFeaturizer
- name: CountVectorsFeaturizer
analyzer: char_wb
min_ngram: 2
max_ngram: 4
- name: CRFEntityExtractor
- name: DucklingHTTPExtractor
# url of the running duckling server
url: http://localhost:8000
# dimensions to extract
dimensions: [ time ]
# allows you to configure the locale, by default the language is used
locale: es_ES
# if not set the default timezone of Duckling is going to be used
# needed to calculate dates from relative expressions like "tomorrow"
timezone: Europe/Madrid
# Timeout for receiving response from http url of the running duckling server
# if not set the default timeout of duckling http url is set to 3 seconds.
timeout: 3
- name: DIETClassifier
entity_recognition: False
epochs: 200
- name: EntitySynonymMapper
- name: ResponseSelector
epochs: 100
policies:
- name: TEDPolicy
max_history: 10
epochs: 20
batch_size:
- 32
- 64
- name: AugmentedMemoizationPolicy
max_history: 6
- name: TwoStageFallbackPolicy
core_threshold: 0.3
nlu_threshold: 0.8
- name: FormPolicy
- name: MappingPolicy
Thx! I’ll try it right now!