Dialogflow training data - dialogflow-es

Training phrases are appearing as Events in Training tab of dialogflow.
get me extra water bottles is training phare in one of my intents.

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How to prevent NER model to overfit entity position with Spacy

I'm building a custom NER model to detect brands in product titles using a well sized dataset of 98k products with their corresponding title, the train contains around 84k records, validation split 10k and test split 3k.
The only problem with the dataset is that 89% of all product titles have the brand as their first words.
When training the NER model from scratch, it gives a good F1 score of 85% after just few epochs (batch size =32), however when testing the model I noticed the follwoign :
The model is strongly biased toward predicting the first word of the title as a brand
The model is very good at detecting brands when they occur as first words, but is quite weak for titles having brands in their middle or end.
I had the idea to solve this by resampling the dataset and removing some brands from some titles as their first word and put it at the end or the middle.
However, I would like to know if there is a technique in NLP that allow the model to not give a large importance to the entity position in the text ? I used dropout of 0.6 but with no success

How do I use Training Phrases in DialogFlow

My Training Phrases do not seem to work in DialogFlow
What I did was I added training phrases for the chatbot. After adding the phrases, I save the intent then try it out on the chatbot. When I type in any of the phrases, it just goes to the fallback intent. Does anyone know how to fix this?
How do I fix this error?

How to automate the task of adding the training phrases to correct intent inside dialogflow using any nlp model

I have an agent on Dialogflow with some fixed number of intents. Currently whenever a phrase does not trigger an intent(i.e trigger a default intent), i manually add the phrase to some existing intent or create a new intent and add the phrase to it.
I want to automate this task of adding the new phrase to a particular intent using some machine learning, nlp classifier.
I have trained a intent classifier to classify the intent based on the phrase, but i am not really sure what my training data should be for this task.
Please refer to following diagram. The diagram shows the thing i want to achieve.
https://drive.google.com/file/d/1-6VRHuxM7E5-7iBVu1uo5SmYZpf6y71l/view?usp=sharing

What's the maximum number of train phrases for each intent in dialogflow?

What's the maximum number of train phases for each intent in dialogflow?
I know there have max intent number 2000 for one agent. but what's the number of the train phrases?
You can have 2000 training phrases per intent.
As Taylor has pointed out, the number of Training Phrases per intent is limited to 2000.
For more such limits and quotas of Dialogflow, you can refer https://dialogflow.com/docs/reference/agent-limits-and-quotas

LUIS not recognizing word parts

I'm testing my LUIS app, I have an Intent called "Services" and other called "Insults" (for filtering insults, right). In "Services" Intent I have Utterances like "I want to see all the services" or "services" but when I test the word "servi" or "serv" it returns the "Insults" Intent instead of the "None" or "Services" Intent.
Let's say that LUIS is getting so strict and is only returning an Intent when I test an utterance that's EXACTLY the same I wrote at the Utterances of that Intent.
What can be causing this?
LUIS learns based on active learning. The algorithm should pick the unlabeled data that should be labelled depending on the confidence of the system in the prediction. In the active learning process, LUIS examines all the endpoint utterances, and selects utterances that it is unsure of. If you label these utterances, train, and publish, then LUIS identifies utterances more accurately. Have you trained any examples under None intent if not please do provide more training examples under "Insults" intent and "None" intent. Hope this helps.

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