Built-in NLP

Natural Language Processing (NLP) allows you to understand and extract meaningful information (intents, entities and traits) out of the messages people send. You can then use this information to identify intent, automate some of your replies, route the conversation to a human via livechat, and collect audience data.

If you are currently leveraging an NLP API, you have to make an extra call when you receive the user message, which adds latency and complexity (example: async, troubleshooting, etc.). With Built-in NLP, intents and entities are automatically detected in every text message that someone sends.

Contents

• Default NLP
  • Entities and Traits
  • Language Support
• Enabling Built-in NLP
• Handling a Message With NLP
• Language Identification
• Customizing NLP via Wit.ai
• Page Inbox Integration

Default NLP

Once Messenger's built-in NLP is enabled for your Facebook Page, it automatically detects meaning and intent in text messages before it is sent to your Messenger experience. The message will be relayed to you as usual, along with any entities detected in the body. See Handling a Message With Entities.

Entities and Traits

By default, Messenger's built-in NLP detects the following information:

Dates and times are automatically localized based on the locale sent in the user's profile.

For example, if someone sends the message, “tomorrow at 2pm” or “2 days before Xmas,” you will get the actual timestamp with the message.

Language Support

By default, Built-in NLP supports the following languages. For other languages, check Customizing NLP via Wit.ai.

Enabling Built-in NLP

To enable Built-in NLP, do the following:

1. Go to your Facebook app's 'Messenger Settings' page.
2. Toggle the "on off" switch to enable/disable Built-in NLP for your app.

Advanced Settings

Built-in NLP also supports the following advanced settings that let you further customize the nlp object included in messages webhook events. To enable/disable these settings, click the 'Advanced Settings` button:

• Versioning: Sets the Wit API version to use.
• N-best: Returns the n-best intent and traits as opposed to only the top one.

Enabling Built-in NLP with the Graph API

You can also use the graph API to enable Built-in NLP programmatically:

curl -i -X POST \
  -d "access_token=$PAGE_APP_ACCESS_TOKEN" \
  "https://graph.facebook.com/v7.0/me/nlp_configs?nlp_enabled=$NLP_ENABLED"

You must append the nlp_enabled parameter which will either enable or disable NLP for that Page.

Handling a Message With NLP

Once Built-in NLP is enabled, you will see an nlp key in the request sent to your message webhook.

For example, the message, "see you tomorrow at 4pm" would include the following information:

{...,
  "entities": {
    "wit$datetime:datetime": [
      {
        "id": "340464963587159",
        "name": "wit$datetime",
        "role": "datetime",
        "start": 8,
        "end": 23,
        "body": "tomorrow at 4pm",
        "confidence": 0.9704,
        "entities": [],
        "type": "value",
        "grain": "hour",
        "value": "2020-06-16T16:00:00.000-07:00",
        "values": [
          {
            "type": "value",
            "grain": "hour",
            "value": "2020-06-16T16:00:00.000-07:00"
          }
        ]
      }
    ]
  },
  "traits": {
    "wit$sentiment": [
      {
        "id": "5ac2b50a-44e4-466e-9d49-bad6bd40092c",
        "value": "neutral",
        "confidence": 0.6162
      }
    ]
  }

For each message, the Messenger Platform will return a mapping of the entities and traits that were captured alongside their structured data. The key pieces of information here are the confidence and the value for each entity or trait.

confidence is a value between 0 and 1 that indicates the probability the parser thinks its recognition is correct.

value is the parser output. For example, 2pm can be converted to an ISO string you can use, like "2017-05-10T14:00:00.000-07:00".

You can learn more about the JSON structure of all the entities and traits in the Wit.ai docs

Example Usage

In your messages webhook, you can update the logic used to respond to messages by taking advantage of Default NLP. For example, if you have a handleMessage() function in your webhook that responds to each message received, you can use the greetings entity to send an appropriate response:

function firstTrait(nlp, name) {
  return nlp && nlp.entities && nlp.traits[name] && nlp.traits[name][0];
}

function handleMessage(message) {
  // check greeting is here and is confident
  const greeting = firstTrait(message.nlp, 'wit$greetings');
  if (greeting && greeting.confidence > 0.8) {
    sendResponse('Hi there!');
  } else { 
    // default logic
  }
}

Replicate this logic for other entities and traits, and you will be on your way to using Built-in NLP!

Language Identification

Language identification enables you to handle multiple languages. Language identification is automatically enabled with built-in NLP. The nlp key in the request sent to your message webhook will return the top detected locales for the message. For example, the message “bonjour les amis” would include:

{
  ...,
  "detected_locales": [
    {
      "locale": "fr_XX",
      "confidence": 0.9986
    },
    {
      "locale": "ar_AR",
      "confidence": 0.0014
    }
  ]
}

confidence level between 0 and 1.

You can then use this information to gracefully handle the incoming requests.

Multilingual support

You can assign a different Wit.ai app (using either a Default Model for the supported languages, or a Custom one) for each language you want to support. When Messenger Platform receives a message, it will first find the top detected language, and use the associated Wit.ai app for extracting the entities. If there isn't a Wit.ai app linked to the top detected language, the default language model will be used.

Customizing NLP via Wit.ai

You can customize Messenger's built-in NLP to detect additional intents, entities and traits in English, as well as in the 132 languages supported by Wit.ai.

To customize NLP with Wit.ai, do the following:

1. Go to your app's 'Messenger Settings' page.
2. In the 'Built-in NLP' section, select one of your subscribed Pages.
3. Add your Wit Server access token. You can find your access token in the Wit App settings.
4. Save your settings.

Updating NLP Settings with the Graph API

You can also update your NLP settings programmatically with a POST request to the Graph API:

curl -i -X POST \
  -d "access_token=$PAGE_APP_ACCESS_TOKEN" \
  "https://graph.facebook.com/v2.8/me/nlp_configs?nlp_enabled=$NLP_ENABLED&&custom_token=$CUSTOM_TOKEN"

The following query parameters are supported:

Page Inbox Integration

The Built-in NLP integration with the Page inbox lets you create a Wit.ai app automatically and bootstrap it with past conversations from your Page directly from the Facebook app console settings. These samples that are compiled into your Wit.ai app are based on real conversations your Page has had with your users.

To try the Built-in NLP Page Inbox feature with your Messenger experience, do the following:

1. In your app settings, go to Messenger > Settings.
2. Enable built-in NLP for your app.
3. In the 'Select a Model' dropdown, select 'Custom'.
4. Click 'Create Wit.ai App'

Random samples from your past conversations in the Page inbox will be compiled, and will show in a newly created Wit app. The samples will be available for tagging in your Wit.ai app immediately.