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Cloud Natural Language API Connector Overview
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The Workflows connector defines the built-in
functions that can be used to access other Google Cloud products within a
workflow.
This page provides an overview of the individual connector.
There is no need to import or load connector libraries in a workflow—connectors
work out of the box when used in a call step.
Cloud Natural Language API
Provides natural language understanding technologies, such as sentiment analysis, entity recognition, entity sentiment analysis, and other text annotations, to developers.
To learn more, see the Cloud Natural Language API documentation .
Cloud Natural Language connector sample
Module: googleapis.language.v1.documents
Functions
analyzeEntities
Finds named entities (currently proper names and common nouns) in the
text along with entity types, salience, mentions for each entity, and
other properties.
analyzeEntitySentiment
Finds entities, similar to AnalyzeEntities in the text and analyzes
sentiment associated with each entity and its mentions.
analyzeSentiment
Analyzes the sentiment of the provided text.
analyzeSyntax
Analyzes the syntax of the text and provides sentence boundaries and
tokenization along with part of speech tags, dependency trees, and other
properties.
annotateText
A convenience method that provides all the features that
analyzeSentiment, analyzeEntities, and analyzeSyntax provide in one
call.
classifyText
Classifies a document into categories.
Module: googleapis.language.v1beta2.documents
Functions
analyzeEntities
Finds named entities (currently proper names and common nouns) in the
text along with entity types, salience, mentions for each entity, and
other properties.
analyzeEntitySentiment
Finds entities, similar to AnalyzeEntities in the text and analyzes
sentiment associated with each entity and its mentions.
analyzeSentiment
Analyzes the sentiment of the provided text.
analyzeSyntax
Analyzes the syntax of the text and provides sentence boundaries and
tokenization along with part of speech tags, dependency trees, and other
properties.
annotateText
A convenience method that provides all syntax, sentiment, entity, and
classification features in one call.
classifyText
Classifies a document into categories.
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Last updated 2025-08-28 UTC.
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[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[],[],null,["# Cloud Natural Language API Connector Overview\n\nThe Workflows connector defines the built-in\nfunctions that can be used to access other Google Cloud products within a\nworkflow.\n\nThis page provides an overview of the individual connector.\nThere is no need to import or load connector libraries in a workflow---connectors\nwork out of the box when used in a call step.\n\nCloud Natural Language API\n--------------------------\n\nProvides natural language understanding technologies, such as sentiment analysis, entity recognition, entity sentiment analysis, and other text annotations, to developers.\nTo learn more, see the [Cloud Natural Language API documentation](https://cloud.google.com/natural-language/).\n\nCloud Natural Language connector sample\n---------------------------------------\n\n### YAML\n\n # This workflow demonstrates how to use the Cloud Language connector:\n # Analyze and classify text samples and log the results\n # Expected output: \"SUCCESS\"\n - init:\n assign:\n - docType: \"PLAIN_TEXT\"\n - analyze_entities:\n call: googleapis.language.v1.documents.analyzeEntities\n args:\n body:\n document:\n type: ${docType}\n language: \"en\"\n content: \"Eiffel Tower\"\n encodingType: \"UTF8\"\n result: response_analyze\n - log_analyze_result:\n call: sys.log\n args:\n data: ${response_analyze}\n severity: \"INFO\"\n - classify_text:\n call: googleapis.language.v1.documents.analyzeSentiment\n args:\n body:\n document:\n type: ${docType}\n language: \"en\"\n content: \"I love Workflows!\"\n encodingType: \"UTF8\"\n result: response_classify\n - log_classify_result:\n call: sys.log\n args:\n data: ${response_classify}\n severity: \"INFO\"\n - the_end:\n return: \"SUCCESS\"\n\n### JSON\n\n [\n {\n \"init\": {\n \"assign\": [\n {\n \"docType\": \"PLAIN_TEXT\"\n }\n ]\n }\n },\n {\n \"analyze_entities\": {\n \"call\": \"googleapis.language.v1.documents.analyzeEntities\",\n \"args\": {\n \"body\": {\n \"document\": {\n \"type\": \"${docType}\",\n \"language\": \"en\",\n \"content\": \"Eiffel Tower\"\n },\n \"encodingType\": \"UTF8\"\n }\n },\n \"result\": \"response_analyze\"\n }\n },\n {\n \"log_analyze_result\": {\n \"call\": \"sys.log\",\n \"args\": {\n \"data\": \"${response_analyze}\",\n \"severity\": \"INFO\"\n }\n }\n },\n {\n \"classify_text\": {\n \"call\": \"googleapis.language.v1.documents.analyzeSentiment\",\n \"args\": {\n \"body\": {\n \"document\": {\n \"type\": \"${docType}\",\n \"language\": \"en\",\n \"content\": \"I love Workflows!\"\n },\n \"encodingType\": \"UTF8\"\n }\n },\n \"result\": \"response_classify\"\n }\n },\n {\n \"log_classify_result\": {\n \"call\": \"sys.log\",\n \"args\": {\n \"data\": \"${response_classify}\",\n \"severity\": \"INFO\"\n }\n }\n },\n {\n \"the_end\": {\n \"return\": \"SUCCESS\"\n }\n }\n ]\n\nModule: googleapis.language.v1.documents\n----------------------------------------\n\nModule: googleapis.language.v1beta2.documents\n---------------------------------------------"]]