Amazon Comprehend · Schema

EntityTypesEvaluationMetrics

Detailed information about the accuracy of an entity recognizer for a specific entity type.

Machine LearningNatural Language ProcessingNLPText Analysis

Properties

Name Type Description
Precision object
Recall object
F1Score object
View JSON Schema on GitHub

JSON Schema

openapi.yml-entity-types-evaluation-metrics-schema.json Raw ↑
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://raw.githubusercontent.com/api-evangelist/amazon-comprehend/refs/heads/main/json-schema/openapi.yml-entity-types-evaluation-metrics-schema.json",
  "title": "EntityTypesEvaluationMetrics",
  "description": "Detailed information about the accuracy of an entity recognizer for a specific entity type. ",
  "type": "object",
  "properties": {
    "Precision": {
      "allOf": [
        {
          "$ref": "#/components/schemas/Double"
        },
        {
          "description": "A measure of the usefulness of the recognizer results for a specific entity type in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones. "
        }
      ]
    },
    "Recall": {
      "allOf": [
        {
          "$ref": "#/components/schemas/Double"
        },
        {
          "description": "A measure of how complete the recognizer results are for a specific entity type in the test data. High recall means that the recognizer returned most of the relevant results."
        }
      ]
    },
    "F1Score": {
      "allOf": [
        {
          "$ref": "#/components/schemas/Double"
        },
        {
          "description": "A measure of how accurate the recognizer results are for a specific entity type in the test data. It is derived from the <code>Precision</code> and <code>Recall</code> values. The <code>F1Score</code> is the harmonic average of the two scores. The highest score is 1, and the worst score is 0. "
        }
      ]
    }
  }
}