Amazon Comprehend · Schema
EntityRecognizerEvaluationMetrics
Detailed information about the accuracy of an entity recognizer.
Machine LearningNatural Language ProcessingNLPText Analysis
Properties
| Name | Type | Description |
|---|---|---|
| Precision | object | |
| Recall | object | |
| F1Score | object |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://raw.githubusercontent.com/api-evangelist/amazon-comprehend/refs/heads/main/json-schema/openapi.yml-entity-recognizer-evaluation-metrics-schema.json",
"title": "EntityRecognizerEvaluationMetrics",
"description": "Detailed information about the accuracy of an entity recognizer. ",
"type": "object",
"properties": {
"Precision": {
"allOf": [
{
"$ref": "#/components/schemas/Double"
},
{
"description": "A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones. "
}
]
},
"Recall": {
"allOf": [
{
"$ref": "#/components/schemas/Double"
},
{
"description": "A measure of how complete the recognizer results are for 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 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. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score. "
}
]
}
}
}