As I mentioned in my previous post, Watson Assistant has a system entity called @sys-name, which allows you to capture a persons name. One issue with this is that it is not available for every language.

In the original post I mention using entity extraction. You can still do this, but the cloud functions feature makes this so much easier.

The instructions for doing this are very well documented, so I intentionally skip over bits. Please use this as a reference.

First I created a Cloud function Action with the following code:

import sys
from watson_developer_cloud import NaturalLanguageUnderstandingV1
from watson_developer_cloud.natural_language_understanding_v1 import Features, EntitiesOptions, KeywordsOptions

nlu = NaturalLanguageUnderstandingV1(
version='2017-02-27',
url='https://gateway-fra.watsonplatform.net/natural-language-understanding/api',
username='USERNAME',
password='PASSWORD')


def main(dict):
    rsp = nlu.analyze(text=dict['input'], features=Features(entities=EntitiesOptions()))

    username = ''
    company = ''

    for entity in rsp['entities']:
        if entity['type'] == 'Person':
            username = entity['text']
        elif entity['type'] == 'Company':
            company = entity['text']

    response = { 
        'name': username, 
        'company': company 
    }

    return response

On the parameters page I set up two parameters “input” and “language“. The language tag is to allow to use different languages where @sys-person may not exist.

On the end point page, you need to copy the API key and break into name:password as per the instructions link. Keep a note of it.

Now in Watson Assistant create a node that triggers and the following json code. Replace username/password with one from cloud function. Alternatively use the proper credentials formatting.

{
    "context": {
        "mycreds": {
            "user": "USERNAME",
            "password": "PASSWORD"
        },
        "nlu_response": ""
    },
    "output": {
        "text": {
            "values": [],
            "selection_policy": "sequential"
        }
    },
    "actions": [
     {
        "name": "simon_test_area/nlu_lookup",
        "type": "server",
        "parameters": {
        "input": "<? input.text ?>",
        "language": "en"
     },
    "credentials": "$mycreds",
    "result_variable": "$nlu_response"
    }
    ]
}

This will execute the cloud function and return the name and company (if they exist). Have this node skip to a child node which will execute the response. For my sample I have:

Name: $nlu_response.name<br>Company: $nlu_response.company

This is what you get back.

Very simple and very powerful. Combine this with Watson Knowledge Studio and you can build intelligence for your domain.