709 lines
28 KiB
JSON
709 lines
28 KiB
JSON
{
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"auth": {
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"oauth2": {
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"scopes": {
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"https://www.googleapis.com/auth/cloud-language": {
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"description": "Apply machine learning models to reveal the structure and meaning of text"
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},
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"https://www.googleapis.com/auth/cloud-platform": {
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"description": "See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account."
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}
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}
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}
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},
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"basePath": "",
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"baseUrl": "https://language.googleapis.com/",
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"batchPath": "batch",
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"canonicalName": "Cloud Natural Language",
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"description": "Provides natural language understanding technologies, such as sentiment analysis, entity recognition, entity sentiment analysis, and other text annotations, to developers.",
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"discoveryVersion": "v1",
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"documentationLink": "https://cloud.google.com/natural-language/",
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"fullyEncodeReservedExpansion": true,
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"icons": {
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"x16": "http://www.google.com/images/icons/product/search-16.gif",
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"x32": "http://www.google.com/images/icons/product/search-32.gif"
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},
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"id": "language:v2",
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"kind": "discovery#restDescription",
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"mtlsRootUrl": "https://language.mtls.googleapis.com/",
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"name": "language",
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"ownerDomain": "google.com",
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"ownerName": "Google",
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"parameters": {
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"$.xgafv": {
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"description": "V1 error format.",
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"enum": [
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"1",
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"2"
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],
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"enumDescriptions": [
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"v1 error format",
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"v2 error format"
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],
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"location": "query",
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"type": "string"
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},
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"access_token": {
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"description": "OAuth access token.",
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"location": "query",
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"type": "string"
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},
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"alt": {
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"default": "json",
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"description": "Data format for response.",
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"enum": [
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"json",
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"media",
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"proto"
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],
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"enumDescriptions": [
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"Responses with Content-Type of application/json",
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"Media download with context-dependent Content-Type",
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"Responses with Content-Type of application/x-protobuf"
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],
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"location": "query",
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"type": "string"
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},
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"callback": {
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"description": "JSONP",
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"location": "query",
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"type": "string"
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},
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"fields": {
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"description": "Selector specifying which fields to include in a partial response.",
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"location": "query",
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"type": "string"
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},
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"key": {
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"description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.",
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"location": "query",
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"type": "string"
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},
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"oauth_token": {
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"description": "OAuth 2.0 token for the current user.",
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"location": "query",
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"type": "string"
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},
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"prettyPrint": {
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"default": "true",
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"description": "Returns response with indentations and line breaks.",
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"location": "query",
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"type": "boolean"
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},
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"quotaUser": {
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"description": "Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.",
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"location": "query",
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"type": "string"
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},
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"uploadType": {
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"description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").",
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"location": "query",
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"type": "string"
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},
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"upload_protocol": {
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"description": "Upload protocol for media (e.g. \"raw\", \"multipart\").",
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"location": "query",
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"type": "string"
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}
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},
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"protocol": "rest",
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"resources": {
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"documents": {
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"methods": {
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"analyzeEntities": {
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"description": "Finds named entities (currently proper names and common nouns) in the text along with entity types, probability, mentions for each entity, and other properties.",
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"flatPath": "v2/documents:analyzeEntities",
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"httpMethod": "POST",
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"id": "language.documents.analyzeEntities",
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"parameterOrder": [],
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"parameters": {},
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"path": "v2/documents:analyzeEntities",
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"request": {
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"$ref": "AnalyzeEntitiesRequest"
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},
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"response": {
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"$ref": "AnalyzeEntitiesResponse"
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},
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"scopes": [
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"https://www.googleapis.com/auth/cloud-language",
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"https://www.googleapis.com/auth/cloud-platform"
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]
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},
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"analyzeSentiment": {
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"description": "Analyzes the sentiment of the provided text.",
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"flatPath": "v2/documents:analyzeSentiment",
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"httpMethod": "POST",
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"id": "language.documents.analyzeSentiment",
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"parameterOrder": [],
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"parameters": {},
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"path": "v2/documents:analyzeSentiment",
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"request": {
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"$ref": "AnalyzeSentimentRequest"
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},
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"response": {
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"$ref": "AnalyzeSentimentResponse"
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},
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"scopes": [
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"https://www.googleapis.com/auth/cloud-language",
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"https://www.googleapis.com/auth/cloud-platform"
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]
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},
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"annotateText": {
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"description": "A convenience method that provides all features in one call.",
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"flatPath": "v2/documents:annotateText",
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"httpMethod": "POST",
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"id": "language.documents.annotateText",
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"parameterOrder": [],
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"parameters": {},
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"path": "v2/documents:annotateText",
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"request": {
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"$ref": "AnnotateTextRequest"
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},
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"response": {
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"$ref": "AnnotateTextResponse"
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},
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"scopes": [
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"https://www.googleapis.com/auth/cloud-language",
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"https://www.googleapis.com/auth/cloud-platform"
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]
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},
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"classifyText": {
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"description": "Classifies a document into categories.",
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"flatPath": "v2/documents:classifyText",
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"httpMethod": "POST",
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"id": "language.documents.classifyText",
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"parameterOrder": [],
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"parameters": {},
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"path": "v2/documents:classifyText",
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"request": {
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"$ref": "ClassifyTextRequest"
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},
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"response": {
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"$ref": "ClassifyTextResponse"
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},
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"scopes": [
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"https://www.googleapis.com/auth/cloud-language",
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"https://www.googleapis.com/auth/cloud-platform"
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]
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},
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"moderateText": {
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"description": "Moderates a document for harmful and sensitive categories.",
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"flatPath": "v2/documents:moderateText",
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"httpMethod": "POST",
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"id": "language.documents.moderateText",
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"parameterOrder": [],
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"parameters": {},
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"path": "v2/documents:moderateText",
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"request": {
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"$ref": "ModerateTextRequest"
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},
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"response": {
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"$ref": "ModerateTextResponse"
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},
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"scopes": [
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"https://www.googleapis.com/auth/cloud-language",
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"https://www.googleapis.com/auth/cloud-platform"
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]
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}
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}
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}
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},
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"revision": "20230812",
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"rootUrl": "https://language.googleapis.com/",
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"schemas": {
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"AnalyzeEntitiesRequest": {
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"description": "The entity analysis request message.",
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"id": "AnalyzeEntitiesRequest",
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"properties": {
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"document": {
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"$ref": "Document",
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"description": "Required. Input document."
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},
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"encodingType": {
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"description": "The encoding type used by the API to calculate offsets.",
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"enum": [
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"NONE",
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"UTF8",
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"UTF16",
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"UTF32"
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],
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"enumDescriptions": [
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"If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively."
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],
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"type": "string"
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}
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},
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"type": "object"
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},
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"AnalyzeEntitiesResponse": {
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"description": "The entity analysis response message.",
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"id": "AnalyzeEntitiesResponse",
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"properties": {
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"entities": {
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"description": "The recognized entities in the input document.",
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"items": {
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"$ref": "Entity"
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},
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"type": "array"
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},
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"languageCode": {
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"description": "The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.",
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"type": "string"
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},
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"languageSupported": {
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"description": "Whether the language is officially supported. The API may still return a response when the language is not supported, but it is on a best effort basis.",
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"type": "boolean"
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}
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},
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"type": "object"
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},
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"AnalyzeSentimentRequest": {
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"description": "The sentiment analysis request message.",
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"id": "AnalyzeSentimentRequest",
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"properties": {
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"document": {
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"$ref": "Document",
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"description": "Required. Input document."
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},
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"encodingType": {
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"description": "The encoding type used by the API to calculate sentence offsets.",
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"enum": [
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"NONE",
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"UTF8",
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"UTF16",
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"UTF32"
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],
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"enumDescriptions": [
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"If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively."
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],
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"type": "string"
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}
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},
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"type": "object"
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},
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"AnalyzeSentimentResponse": {
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"description": "The sentiment analysis response message.",
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"id": "AnalyzeSentimentResponse",
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"properties": {
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"documentSentiment": {
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"$ref": "Sentiment",
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"description": "The overall sentiment of the input document."
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},
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"languageCode": {
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"description": "The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.",
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"type": "string"
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},
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"languageSupported": {
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"description": "Whether the language is officially supported. The API may still return a response when the language is not supported, but it is on a best effort basis.",
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"type": "boolean"
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},
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"sentences": {
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"description": "The sentiment for all the sentences in the document.",
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"items": {
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"$ref": "Sentence"
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},
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"type": "array"
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}
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},
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"type": "object"
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},
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"AnnotateTextRequest": {
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"description": "The request message for the text annotation API, which can perform multiple analysis types in one call.",
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"id": "AnnotateTextRequest",
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"properties": {
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"document": {
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"$ref": "Document",
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"description": "Required. Input document."
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},
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"encodingType": {
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"description": "The encoding type used by the API to calculate offsets.",
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"enum": [
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"NONE",
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"UTF8",
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"UTF16",
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"UTF32"
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],
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"enumDescriptions": [
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"If `EncodingType` is not specified, encoding-dependent information (such as `begin_offset`) will be set at `-1`.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-8 encoding of the input. C++ and Go are examples of languages that use this encoding natively.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-16 encoding of the input. Java and JavaScript are examples of languages that use this encoding natively.",
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"Encoding-dependent information (such as `begin_offset`) is calculated based on the UTF-32 encoding of the input. Python is an example of a language that uses this encoding natively."
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],
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"type": "string"
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},
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"features": {
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"$ref": "Features",
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"description": "Required. The enabled features."
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}
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},
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"type": "object"
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},
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"AnnotateTextResponse": {
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"description": "The text annotations response message.",
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"id": "AnnotateTextResponse",
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"properties": {
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"categories": {
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"description": "Categories identified in the input document.",
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"items": {
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"$ref": "ClassificationCategory"
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},
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"type": "array"
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},
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"documentSentiment": {
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"$ref": "Sentiment",
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"description": "The overall sentiment for the document. Populated if the user enables AnnotateTextRequest.Features.extract_document_sentiment."
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},
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"entities": {
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"description": "Entities, along with their semantic information, in the input document. Populated if the user enables AnnotateTextRequest.Features.extract_entities or AnnotateTextRequest.Features.extract_entity_sentiment.",
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"items": {
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"$ref": "Entity"
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},
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"type": "array"
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},
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"languageCode": {
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"description": "The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.",
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"type": "string"
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},
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"languageSupported": {
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"description": "Whether the language is officially supported by all requested features. The API may still return a response when the language is not supported, but it is on a best effort basis.",
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"type": "boolean"
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},
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"moderationCategories": {
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"description": "Harmful and sensitive categories identified in the input document.",
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"items": {
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"$ref": "ClassificationCategory"
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},
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"type": "array"
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},
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"sentences": {
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"description": "Sentences in the input document. Populated if the user enables AnnotateTextRequest.Features.extract_document_sentiment.",
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"items": {
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"$ref": "Sentence"
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},
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"type": "array"
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}
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},
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"type": "object"
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},
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"ClassificationCategory": {
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"description": "Represents a category returned from the text classifier.",
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"id": "ClassificationCategory",
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"properties": {
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"confidence": {
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"description": "The classifier's confidence of the category. Number represents how certain the classifier is that this category represents the given text.",
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"format": "float",
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"type": "number"
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},
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"name": {
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"description": "The name of the category representing the document.",
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"type": "string"
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}
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},
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"type": "object"
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},
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"ClassifyTextRequest": {
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"description": "The document classification request message.",
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"id": "ClassifyTextRequest",
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"properties": {
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"document": {
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"$ref": "Document",
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"description": "Required. Input document."
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}
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},
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"type": "object"
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},
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"ClassifyTextResponse": {
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"description": "The document classification response message.",
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"id": "ClassifyTextResponse",
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"properties": {
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"categories": {
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"description": "Categories representing the input document.",
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"items": {
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"$ref": "ClassificationCategory"
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},
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"type": "array"
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},
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"languageCode": {
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"description": "The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.",
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"type": "string"
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},
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"languageSupported": {
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"description": "Whether the language is officially supported. The API may still return a response when the language is not supported, but it is on a best effort basis.",
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"type": "boolean"
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}
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},
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"type": "object"
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},
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"Document": {
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"description": "Represents the input to API methods.",
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"id": "Document",
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"properties": {
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"content": {
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"description": "The content of the input in string format. Cloud audit logging exempt since it is based on user data.",
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"type": "string"
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},
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"gcsContentUri": {
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"description": "The Google Cloud Storage URI where the file content is located. This URI must be of the form: gs://bucket_name/object_name. For more details, see https://cloud.google.com/storage/docs/reference-uris. NOTE: Cloud Storage object versioning is not supported.",
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"type": "string"
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},
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"languageCode": {
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"description": "Optional. The language of the document (if not specified, the language is automatically detected). Both ISO and BCP-47 language codes are accepted. [Language Support](https://cloud.google.com/natural-language/docs/languages) lists currently supported languages for each API method. If the language (either specified by the caller or automatically detected) is not supported by the called API method, an `INVALID_ARGUMENT` error is returned.",
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"type": "string"
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},
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"type": {
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"description": "Required. If the type is not set or is `TYPE_UNSPECIFIED`, returns an `INVALID_ARGUMENT` error.",
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"enum": [
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"TYPE_UNSPECIFIED",
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"PLAIN_TEXT",
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"HTML"
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],
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"enumDescriptions": [
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"The content type is not specified.",
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"Plain text",
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"HTML"
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],
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"type": "string"
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}
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},
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"type": "object"
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},
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"Entity": {
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"description": "Represents a phrase in the text that is a known entity, such as a person, an organization, or location. The API associates information, such as probability and mentions, with entities.",
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"id": "Entity",
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"properties": {
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"mentions": {
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"description": "The mentions of this entity in the input document. The API currently supports proper noun mentions.",
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"items": {
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"$ref": "EntityMention"
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},
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"type": "array"
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},
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"metadata": {
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"additionalProperties": {
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"type": "string"
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},
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"description": "Metadata associated with the entity. For most entity types, the metadata is a Wikipedia URL (`wikipedia_url`) and Knowledge Graph MID (`mid`), if they are available. For the metadata associated with other entity types, see the Type table below.",
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"type": "object"
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},
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"name": {
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"description": "The representative name for the entity.",
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"type": "string"
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},
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"sentiment": {
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"$ref": "Sentiment",
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"description": "For calls to AnalyzeEntitySentiment or if AnnotateTextRequest.Features.extract_entity_sentiment is set to true, this field will contain the aggregate sentiment expressed for this entity in the provided document."
|
|
},
|
|
"type": {
|
|
"description": "The entity type.",
|
|
"enum": [
|
|
"UNKNOWN",
|
|
"PERSON",
|
|
"LOCATION",
|
|
"ORGANIZATION",
|
|
"EVENT",
|
|
"WORK_OF_ART",
|
|
"CONSUMER_GOOD",
|
|
"OTHER",
|
|
"PHONE_NUMBER",
|
|
"ADDRESS",
|
|
"DATE",
|
|
"NUMBER",
|
|
"PRICE"
|
|
],
|
|
"enumDescriptions": [
|
|
"Unknown",
|
|
"Person",
|
|
"Location",
|
|
"Organization",
|
|
"Event",
|
|
"Artwork",
|
|
"Consumer product",
|
|
"Other types of entities",
|
|
"Phone number The metadata lists the phone number, formatted according to local convention, plus whichever additional elements appear in the text: * `number` - the actual number, broken down into sections as per local convention * `national_prefix` - country code, if detected * `area_code` - region or area code, if detected * `extension` - phone extension (to be dialed after connection), if detected",
|
|
"Address The metadata identifies the street number and locality plus whichever additional elements appear in the text: * `street_number` - street number * `locality` - city or town * `street_name` - street/route name, if detected * `postal_code` - postal code, if detected * `country` - country, if detected< * `broad_region` - administrative area, such as the state, if detected * `narrow_region` - smaller administrative area, such as county, if detected * `sublocality` - used in Asian addresses to demark a district within a city, if detected",
|
|
"Date The metadata identifies the components of the date: * `year` - four digit year, if detected * `month` - two digit month number, if detected * `day` - two digit day number, if detected",
|
|
"Number The metadata is the number itself.",
|
|
"Price The metadata identifies the `value` and `currency`."
|
|
],
|
|
"type": "string"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"EntityMention": {
|
|
"description": "Represents a mention for an entity in the text. Currently, proper noun mentions are supported.",
|
|
"id": "EntityMention",
|
|
"properties": {
|
|
"probability": {
|
|
"description": "Probability score associated with the entity. The score shows the probability of the entity mention being the entity type. The score is in (0, 1] range.",
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"sentiment": {
|
|
"$ref": "Sentiment",
|
|
"description": "For calls to AnalyzeEntitySentiment or if AnnotateTextRequest.Features.extract_entity_sentiment is set to true, this field will contain the sentiment expressed for this mention of the entity in the provided document."
|
|
},
|
|
"text": {
|
|
"$ref": "TextSpan",
|
|
"description": "The mention text."
|
|
},
|
|
"type": {
|
|
"description": "The type of the entity mention.",
|
|
"enum": [
|
|
"TYPE_UNKNOWN",
|
|
"PROPER",
|
|
"COMMON"
|
|
],
|
|
"enumDescriptions": [
|
|
"Unknown",
|
|
"Proper name",
|
|
"Common noun (or noun compound)"
|
|
],
|
|
"type": "string"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"Features": {
|
|
"description": "All available features. Setting each one to true will enable that specific analysis for the input.",
|
|
"id": "Features",
|
|
"properties": {
|
|
"classifyText": {
|
|
"description": "Optional. Classify the full document into categories.",
|
|
"type": "boolean"
|
|
},
|
|
"extractDocumentSentiment": {
|
|
"description": "Optional. Extract document-level sentiment.",
|
|
"type": "boolean"
|
|
},
|
|
"extractEntities": {
|
|
"description": "Optional. Extract entities.",
|
|
"type": "boolean"
|
|
},
|
|
"moderateText": {
|
|
"description": "Optional. Moderate the document for harmful and sensitive categories.",
|
|
"type": "boolean"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"ModerateTextRequest": {
|
|
"description": "The document moderation request message.",
|
|
"id": "ModerateTextRequest",
|
|
"properties": {
|
|
"document": {
|
|
"$ref": "Document",
|
|
"description": "Required. Input document."
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"ModerateTextResponse": {
|
|
"description": "The document moderation response message.",
|
|
"id": "ModerateTextResponse",
|
|
"properties": {
|
|
"languageCode": {
|
|
"description": "The language of the text, which will be the same as the language specified in the request or, if not specified, the automatically-detected language. See Document.language field for more details.",
|
|
"type": "string"
|
|
},
|
|
"languageSupported": {
|
|
"description": "Whether the language is officially supported. The API may still return a response when the language is not supported, but it is on a best effort basis.",
|
|
"type": "boolean"
|
|
},
|
|
"moderationCategories": {
|
|
"description": "Harmful and sensitive categories representing the input document.",
|
|
"items": {
|
|
"$ref": "ClassificationCategory"
|
|
},
|
|
"type": "array"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"Sentence": {
|
|
"description": "Represents a sentence in the input document.",
|
|
"id": "Sentence",
|
|
"properties": {
|
|
"sentiment": {
|
|
"$ref": "Sentiment",
|
|
"description": "For calls to AnalyzeSentiment or if AnnotateTextRequest.Features.extract_document_sentiment is set to true, this field will contain the sentiment for the sentence."
|
|
},
|
|
"text": {
|
|
"$ref": "TextSpan",
|
|
"description": "The sentence text."
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"Sentiment": {
|
|
"description": "Represents the feeling associated with the entire text or entities in the text.",
|
|
"id": "Sentiment",
|
|
"properties": {
|
|
"magnitude": {
|
|
"description": "A non-negative number in the [0, +inf) range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).",
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"score": {
|
|
"description": "Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).",
|
|
"format": "float",
|
|
"type": "number"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"Status": {
|
|
"description": "The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).",
|
|
"id": "Status",
|
|
"properties": {
|
|
"code": {
|
|
"description": "The status code, which should be an enum value of google.rpc.Code.",
|
|
"format": "int32",
|
|
"type": "integer"
|
|
},
|
|
"details": {
|
|
"description": "A list of messages that carry the error details. There is a common set of message types for APIs to use.",
|
|
"items": {
|
|
"additionalProperties": {
|
|
"description": "Properties of the object. Contains field @type with type URL.",
|
|
"type": "any"
|
|
},
|
|
"type": "object"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"message": {
|
|
"description": "A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.",
|
|
"type": "string"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"TextSpan": {
|
|
"description": "Represents a text span in the input document.",
|
|
"id": "TextSpan",
|
|
"properties": {
|
|
"beginOffset": {
|
|
"description": "The API calculates the beginning offset of the content in the original document according to the EncodingType specified in the API request.",
|
|
"format": "int32",
|
|
"type": "integer"
|
|
},
|
|
"content": {
|
|
"description": "The content of the text span, which is a substring of the document.",
|
|
"type": "string"
|
|
}
|
|
},
|
|
"type": "object"
|
|
}
|
|
},
|
|
"servicePath": "",
|
|
"title": "Cloud Natural Language API",
|
|
"version": "v2",
|
|
"version_module": true
|
|
} |