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<h1><a href="language_v2.html">Cloud Natural Language API</a> . <a href="language_v2.documents.html">documents</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
<code><a href="#analyzeEntities">analyzeEntities(body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Finds named entities (currently proper names and common nouns) in the text along with entity types, probability, mentions for each entity, and other properties.</p>
<p class="toc_element">
<code><a href="#analyzeSentiment">analyzeSentiment(body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Analyzes the sentiment of the provided text.</p>
<p class="toc_element">
<code><a href="#annotateText">annotateText(body=None, x__xgafv=None)</a></code></p>
<p class="firstline">A convenience method that provides all features in one call.</p>
<p class="toc_element">
<code><a href="#classifyText">classifyText(body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Classifies a document into categories.</p>
<p class="toc_element">
<code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
<code><a href="#moderateText">moderateText(body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Moderates a document for harmful and sensitive categories.</p>
<h3>Method Details</h3>
<div class="method">
<code class="details" id="analyzeEntities">analyzeEntities(body=None, x__xgafv=None)</code>
<pre>Finds named entities (currently proper names and common nouns) in the text along with entity types, probability, mentions for each entity, and other properties.
Args:
body: object, The request body.
The object takes the form of:
{ # The entity analysis request message.
"document": { # Represents the input to API methods. # Required. Input document.
"content": "A String", # The content of the input in string format. Cloud audit logging exempt since it is based on user data.
"gcsContentUri": "A String", # 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.
"languageCode": "A String", # 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.
"type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, returns an `INVALID_ARGUMENT` error.
},
"encodingType": "A String", # The encoding type used by the API to calculate offsets.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The entity analysis response message.
"entities": [ # The recognized entities in the input document.
{ # 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.
"mentions": [ # The mentions of this entity in the input document. The API currently supports proper noun mentions.
{ # Represents a mention for an entity in the text. Currently, proper noun mentions are supported.
"probability": 3.14, # 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.
"sentiment": { # Represents the feeling associated with the entire text or entities in the text. # For calls to AnalyzeEntitySentiment this field will contain the sentiment expressed for this mention of the entity in the provided document.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"text": { # Represents a text span in the input document. # The mention text.
"beginOffset": 42, # The API calculates the beginning offset of the content in the original document according to the EncodingType specified in the API request.
"content": "A String", # The content of the text span, which is a substring of the document.
},
"type": "A String", # The type of the entity mention.
},
],
"metadata": { # Metadata associated with the entity. For the metadata associated with other entity types, see the Type table below.
"a_key": "A String",
},
"name": "A String", # The representative name for the entity.
"sentiment": { # Represents the feeling associated with the entire text or entities in the text. # For calls to AnalyzeEntitySentiment this field will contain the aggregate sentiment expressed for this entity in the provided document.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"type": "A String", # The entity type.
},
],
"languageCode": "A String", # 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_code field for more details.
"languageSupported": True or False, # 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.
}</pre>
</div>
<div class="method">
<code class="details" id="analyzeSentiment">analyzeSentiment(body=None, x__xgafv=None)</code>
<pre>Analyzes the sentiment of the provided text.
Args:
body: object, The request body.
The object takes the form of:
{ # The sentiment analysis request message.
"document": { # Represents the input to API methods. # Required. Input document.
"content": "A String", # The content of the input in string format. Cloud audit logging exempt since it is based on user data.
"gcsContentUri": "A String", # 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.
"languageCode": "A String", # 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.
"type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, returns an `INVALID_ARGUMENT` error.
},
"encodingType": "A String", # The encoding type used by the API to calculate sentence offsets.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The sentiment analysis response message.
"documentSentiment": { # Represents the feeling associated with the entire text or entities in the text. # The overall sentiment of the input document.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"languageCode": "A String", # 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_code field for more details.
"languageSupported": True or False, # 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.
"sentences": [ # The sentiment for all the sentences in the document.
{ # Represents a sentence in the input document.
"sentiment": { # Represents the feeling associated with the entire text or entities in the text. # For calls to AnalyzeSentiment or if AnnotateTextRequest.Features.extract_document_sentiment is set to true, this field will contain the sentiment for the sentence.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"text": { # Represents a text span in the input document. # The sentence text.
"beginOffset": 42, # The API calculates the beginning offset of the content in the original document according to the EncodingType specified in the API request.
"content": "A String", # The content of the text span, which is a substring of the document.
},
},
],
}</pre>
</div>
<div class="method">
<code class="details" id="annotateText">annotateText(body=None, x__xgafv=None)</code>
<pre>A convenience method that provides all features in one call.
Args:
body: object, The request body.
The object takes the form of:
{ # The request message for the text annotation API, which can perform multiple analysis types in one call.
"document": { # Represents the input to API methods. # Required. Input document.
"content": "A String", # The content of the input in string format. Cloud audit logging exempt since it is based on user data.
"gcsContentUri": "A String", # 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.
"languageCode": "A String", # 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.
"type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, returns an `INVALID_ARGUMENT` error.
},
"encodingType": "A String", # The encoding type used by the API to calculate offsets.
"features": { # All available features. Setting each one to true will enable that specific analysis for the input. # Required. The enabled features.
"classifyText": True or False, # Optional. Classify the full document into categories.
"extractDocumentSentiment": True or False, # Optional. Extract document-level sentiment.
"extractEntities": True or False, # Optional. Extract entities.
"moderateText": True or False, # Optional. Moderate the document for harmful and sensitive categories.
},
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The text annotations response message.
"categories": [ # Categories identified in the input document.
{ # Represents a category returned from the text classifier.
"confidence": 3.14, # The classifier's confidence of the category. Number represents how certain the classifier is that this category represents the given text.
"name": "A String", # The name of the category representing the document.
"severity": 3.14, # Optional. The classifier's severity of the category. This is only present when the ModerateTextRequest.ModelVersion is set to MODEL_VERSION_2, and the corresponding category has a severity score.
},
],
"documentSentiment": { # Represents the feeling associated with the entire text or entities in the text. # The overall sentiment for the document. Populated if the user enables AnnotateTextRequest.Features.extract_document_sentiment.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"entities": [ # Entities, along with their semantic information, in the input document. Populated if the user enables AnnotateTextRequest.Features.extract_entities .
{ # 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.
"mentions": [ # The mentions of this entity in the input document. The API currently supports proper noun mentions.
{ # Represents a mention for an entity in the text. Currently, proper noun mentions are supported.
"probability": 3.14, # 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.
"sentiment": { # Represents the feeling associated with the entire text or entities in the text. # For calls to AnalyzeEntitySentiment this field will contain the sentiment expressed for this mention of the entity in the provided document.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"text": { # Represents a text span in the input document. # The mention text.
"beginOffset": 42, # The API calculates the beginning offset of the content in the original document according to the EncodingType specified in the API request.
"content": "A String", # The content of the text span, which is a substring of the document.
},
"type": "A String", # The type of the entity mention.
},
],
"metadata": { # Metadata associated with the entity. For the metadata associated with other entity types, see the Type table below.
"a_key": "A String",
},
"name": "A String", # The representative name for the entity.
"sentiment": { # Represents the feeling associated with the entire text or entities in the text. # For calls to AnalyzeEntitySentiment this field will contain the aggregate sentiment expressed for this entity in the provided document.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"type": "A String", # The entity type.
},
],
"languageCode": "A String", # 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_code field for more details.
"languageSupported": True or False, # 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.
"moderationCategories": [ # Harmful and sensitive categories identified in the input document.
{ # Represents a category returned from the text classifier.
"confidence": 3.14, # The classifier's confidence of the category. Number represents how certain the classifier is that this category represents the given text.
"name": "A String", # The name of the category representing the document.
"severity": 3.14, # Optional. The classifier's severity of the category. This is only present when the ModerateTextRequest.ModelVersion is set to MODEL_VERSION_2, and the corresponding category has a severity score.
},
],
"sentences": [ # Sentences in the input document. Populated if the user enables AnnotateTextRequest.Features.extract_document_sentiment.
{ # Represents a sentence in the input document.
"sentiment": { # Represents the feeling associated with the entire text or entities in the text. # For calls to AnalyzeSentiment or if AnnotateTextRequest.Features.extract_document_sentiment is set to true, this field will contain the sentiment for the sentence.
"magnitude": 3.14, # A non-negative number in the [0, +inf] range, which represents the absolute magnitude of sentiment regardless of score (positive or negative).
"score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
},
"text": { # Represents a text span in the input document. # The sentence text.
"beginOffset": 42, # The API calculates the beginning offset of the content in the original document according to the EncodingType specified in the API request.
"content": "A String", # The content of the text span, which is a substring of the document.
},
},
],
}</pre>
</div>
<div class="method">
<code class="details" id="classifyText">classifyText(body=None, x__xgafv=None)</code>
<pre>Classifies a document into categories.
Args:
body: object, The request body.
The object takes the form of:
{ # The document classification request message.
"document": { # Represents the input to API methods. # Required. Input document.
"content": "A String", # The content of the input in string format. Cloud audit logging exempt since it is based on user data.
"gcsContentUri": "A String", # 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.
"languageCode": "A String", # 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.
"type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, returns an `INVALID_ARGUMENT` error.
},
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The document classification response message.
"categories": [ # Categories representing the input document.
{ # Represents a category returned from the text classifier.
"confidence": 3.14, # The classifier's confidence of the category. Number represents how certain the classifier is that this category represents the given text.
"name": "A String", # The name of the category representing the document.
"severity": 3.14, # Optional. The classifier's severity of the category. This is only present when the ModerateTextRequest.ModelVersion is set to MODEL_VERSION_2, and the corresponding category has a severity score.
},
],
"languageCode": "A String", # 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_code field for more details.
"languageSupported": True or False, # 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.
}</pre>
</div>
<div class="method">
<code class="details" id="close">close()</code>
<pre>Close httplib2 connections.</pre>
</div>
<div class="method">
<code class="details" id="moderateText">moderateText(body=None, x__xgafv=None)</code>
<pre>Moderates a document for harmful and sensitive categories.
Args:
body: object, The request body.
The object takes the form of:
{ # The document moderation request message.
"document": { # Represents the input to API methods. # Required. Input document.
"content": "A String", # The content of the input in string format. Cloud audit logging exempt since it is based on user data.
"gcsContentUri": "A String", # 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.
"languageCode": "A String", # 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.
"type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, returns an `INVALID_ARGUMENT` error.
},
"modelVersion": "A String", # Optional. The model version to use for ModerateText.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The document moderation response message.
"languageCode": "A String", # 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_code field for more details.
"languageSupported": True or False, # 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.
"moderationCategories": [ # Harmful and sensitive categories representing the input document.
{ # Represents a category returned from the text classifier.
"confidence": 3.14, # The classifier's confidence of the category. Number represents how certain the classifier is that this category represents the given text.
"name": "A String", # The name of the category representing the document.
"severity": 3.14, # Optional. The classifier's severity of the category. This is only present when the ModerateTextRequest.ModelVersion is set to MODEL_VERSION_2, and the corresponding category has a severity score.
},
],
}</pre>
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