customEntities()

customEntities() -> { collection of customEntities}

This method returns a collection of custom entities and has the same behavior as the entities() method. As with the named entities, custom entities can be extracted from a winkNLP document or a sentence item.

In case no matches are found for the patterns defined in the learnCustomEntities() method, then the customEntities() method returns an empty array. Similarly, if the learnCustomEntities() method is not called at all and you still call customEntities(), it will return an empty array.

You can chain it further with other winkNLP methods like each(), length(), filter(), etc. However, to get the output in a JavaScript data type, you need to follow this API with out().

Example:

const text = 'I wish to order 1 small classic with corn topping and 2 large supreme with Olives, Onion topping.';
const pizza = [
  { name: 'Category', patterns: [ '[Classic|Supreme|Extravaganza|Favorite]' ] },
  { name: 'Qty', patterns: [ 'CARDINAL' ] },
  { name: 'Topping', patterns: [ '[Corn|Capsicum|Onion|Peppers|Cheese|Jalapenos|Olives]' ] },
  { name: 'Size', patterns: [ '[Small|Medium|Large|Chairman|Wedge]' ] }
 ];

nlp.learnCustomEntities( pizza, {matchValue: false, usePOS: true, useEntity: true } );

const doc = nlp.readDoc( text );

// Custom Entities in winkNLP doc
const customEntities = doc.customEntities().out( its.detail );
console.log( customEntities );
// -> [ { value: '1', type: 'Qty' },
//      { value: 'small', type: 'Size' },
//      { value: 'classic', type: 'Category' },
//      { value: 'corn', type: 'Topping' },
//      { value: '2', type: 'Qty' },
//      { value: 'large', type: 'Size' },
//      { value: 'supreme', type: 'Category' },
//      { value: 'Olives', type: 'Topping' },
//      { value: 'Onion', type: 'Topping' } ]