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XQuery cts:entity

MarkLogic 9 Product Documentation
cts.entity

cts.entity(
   id as String,
   normalizedText as String,
   text as String,
   type as String
) as cts.entity

Summary

Returns a cts:entity object. This is an opaque object you can use to build an entity dictionary.

Parameters
id A unique ID for the entity. A unique entity may have multiple entries in the dictionary with different matching words: the unique ID ties them all together. For entities created from a SKOS ontology this could be the URI of the Concept.
normalizedText The normalized form of the entity. For entities created from a SKOS ontology this could be the preferred label of the Concept.
text The word (or phrase) to match during entity extraction. This will be an exact match, unless the dictionary was created with the "case-insensitive" option, in which case the string is matched with case folding. For entities created from a SKOS ontology this could be a label or alternative label for the Concept.
type The type of the entity. For entities created from a SKOS ontology this could be the id of the top concept for the matching Concept, or its preferred label.

See Also

Example

const entries = [];
for (let alt of ['ACA', 'Obamacare', 'Affordable Care Act']) {
  entries.push(cts.entity('E1', 'ACA', alt, 'Law'));
}
const dictionary = cts.entityDictionary(entries);
const inputNode = new NodeBuilder()
                    .addElement('node', 'ACA is often called Obamacare')
                    .toNode();
const resultBuilder = new NodeBuilder();
cts.entityHighlight(inputNode,
  function(builder, entityType, text, normText, entityId, node, start) {
      builder.startElement(entityType)
              .addAttribute('norm', normText)
              .addText(text)
             .endElement(); 
  },
  resultBuilder, dictionary);
resultBuilder.toNode();

// Returns the following output:
//
// <node><Law norm="ACA">ACA</Law> is often called <Law norm="ACA">Obamacare</Law></node>

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