CODEWITHSUNDEEP
rasanamed-entity-extractionnlu
Alberto Sánchez Ruiz
Alberto Sánchez Ruiz

Reputation: 95

Problem with RASA Entity Extraction in a translation NLU Model

I'm new to RASA framework. I'm trying to develop a Spanish NLU model capable of classifying a user message in 4 different intents ("translation", "definition", "synonym" and "pronunciation") and recognising entities (in this case, my entities could potentially be every word or expression).

So for example, the user could give the following input:

"Cómo se traduce estación de tren al inglés" (How to translate train station into English)

So the word or expression could be any word or words and they could have any length. What's the best way to solve this problem? What entity extractor could I use and what parameter should I try?

Thanks in advance!

Upvotes: 1

Views: 573

Answers (1)

Ievgen
Ievgen

Reputation: 4443

You cannot expect that any unknown sentence or words will be properly interpreted by RASA. You are responsible to train AI with a specific Model contains exact sentences and RASA will give you some probabilities whether something similar is asked.

You should define and categorize general sentences that might be asked:

Example 1:

  • Where is the {train station}?
  • How to find a {train station}?

Results:

  • Action: location
  • Variable: {train station} (can be anything here)

Example 2:

  • How to translate {word}
  • I would like to translate {word} in {English}
  • How would you say in {English} {word}
  • Translate {word} {English}

Results:

  • Action: translation
  • Variables: {English} {word}

RASA will work for you if you will be able to categorize all possible cases of the sentences thatmight be asked

Upvotes: 1

Related Questions