analyzeEntities(body, x__xgafv=None)
Finds named entities (currently finds proper names) in the text,
analyzeSentiment(body, x__xgafv=None)
Analyzes the sentiment of the provided text.
annotateText(body, x__xgafv=None)
A convenience method that provides all the features that analyzeSentiment,
analyzeEntities(body, x__xgafv=None)
Finds named entities (currently finds proper names) in the text, entity types, salience, mentions for each entity, and other properties. Args: body: object, The request body. (required) The object takes the form of: { # The entity analysis request message. "document": { # ################################################################ # # Input document. # # Represents the input to API methods. "content": "A String", # The content of the input in string format. "type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, # returns an `INVALID_ARGUMENT` error. "language": "A String", # The language of the document (if not specified, the language is # automatically detected). Both ISO and BCP-47 language codes are # accepted.
# **Current Language Restrictions:** # # * Only English, Spanish, and Japanese textual content # are supported, with the following additional restriction: # * `analyzeSentiment` only supports English text. # 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. "gcsContentUri": "A String", # The Google Cloud Storage URI where the file content is located. }, "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 salience and mentions, with entities. "type": "A String", # The entity type. "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. "text": { # Represents an output piece of text. # The mention text. "content": "A String", # The content of the output 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. }, }, ], "salience": 3.14, # The salience score associated with the entity in the [0, 1.0] range. # # The salience score for an entity provides information about the # importance or centrality of that entity to the entire document text. # Scores closer to 0 are less salient, while scores closer to 1.0 are highly # salient. "name": "A String", # The representative name for the entity. "metadata": { # Metadata associated with the entity. # # Currently, only Wikipedia URLs are provided, if available. # The associated key is "wikipedia_url". "a_key": "A String", }, }, ], "language": "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 field for more details. }
analyzeSentiment(body, x__xgafv=None)
Analyzes the sentiment of the provided text. Args: body: object, The request body. (required) The object takes the form of: { # The sentiment analysis request message. "document": { # ################################################################ # # Input document. Currently, `analyzeSentiment` only supports English text # (Document.language="EN"). # # Represents the input to API methods. "content": "A String", # The content of the input in string format. "type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, # returns an `INVALID_ARGUMENT` error. "language": "A String", # The language of the document (if not specified, the language is # automatically detected). Both ISO and BCP-47 language codes are # accepted.
# **Current Language Restrictions:** # # * Only English, Spanish, and Japanese textual content # are supported, with the following additional restriction: # * `analyzeSentiment` only supports English text. # 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. "gcsContentUri": "A String", # The Google Cloud Storage URI where the file content is located. }, } 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 overall sentiment of the input document. # the text. "polarity": 3.14, # Polarity of the sentiment in the [-1.0, 1.0] range. Larger numbers # represent more positive sentiments. "magnitude": 3.14, # A non-negative number in the [0, +inf) range, which represents # the absolute magnitude of sentiment regardless of polarity (positive or # negative). }, "language": "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. }
annotateText(body, x__xgafv=None)
A convenience method that provides all the features that analyzeSentiment, analyzeEntities, and analyzeSyntax provide in one call. Args: body: object, The request body. (required) The object takes the form of: { # The request message for the text annotation API, which can perform multiple # analysis types (sentiment, entities, and syntax) in one call. "document": { # ################################################################ # # Input document. # # Represents the input to API methods. "content": "A String", # The content of the input in string format. "type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`, # returns an `INVALID_ARGUMENT` error. "language": "A String", # The language of the document (if not specified, the language is # automatically detected). Both ISO and BCP-47 language codes are # accepted.
# **Current Language Restrictions:** # # * Only English, Spanish, and Japanese textual content # are supported, with the following additional restriction: # * `analyzeSentiment` only supports English text. # 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. "gcsContentUri": "A String", # The Google Cloud Storage URI where the file content is located. }, "encodingType": "A String", # The encoding type used by the API to calculate offsets. "features": { # All available features for sentiment, syntax, and semantic analysis. # The enabled features. # Setting each one to true will enable that specific analysis for the input. "extractSyntax": True or False, # Extract syntax information. "extractEntities": True or False, # Extract entities. "extractDocumentSentiment": True or False, # Extract document-level sentiment. }, } 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. "tokens": [ # Tokens, along with their syntactic information, in the input document. # Populated if the user enables # AnnotateTextRequest.Features.extract_syntax. { # Represents the smallest syntactic building block of the text. "text": { # Represents an output piece of text. # The token text. "content": "A String", # The content of the output 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. }, "dependencyEdge": { # Represents dependency parse tree information for a token. # Dependency tree parse for this token. "headTokenIndex": 42, # Represents the head of this token in the dependency tree. # This is the index of the token which has an arc going to this token. # The index is the position of the token in the array of tokens returned # by the API method. If this token is a root token, then the # `head_token_index` is its own index. "label": "A String", # The parse label for the token. }, "partOfSpeech": { # Represents part of speech information for a token. # Parts of speech tag for this token. "tag": "A String", # The part of speech tag. }, "lemma": "A String", # [Lemma](https://en.wikipedia.org/wiki/Lemma_(morphology)) # of the token. }, ], "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 salience and mentions, with entities. "type": "A String", # The entity type. "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. "text": { # Represents an output piece of text. # The mention text. "content": "A String", # The content of the output 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. }, }, ], "salience": 3.14, # The salience score associated with the entity in the [0, 1.0] range. # # The salience score for an entity provides information about the # importance or centrality of that entity to the entire document text. # Scores closer to 0 are less salient, while scores closer to 1.0 are highly # salient. "name": "A String", # The representative name for the entity. "metadata": { # Metadata associated with the entity. # # Currently, only Wikipedia URLs are provided, if available. # The associated key is "wikipedia_url". "a_key": "A String", }, }, ], "documentSentiment": { # Represents the feeling associated with the entire text or entities in # The overall sentiment for the document. Populated if the user enables # AnnotateTextRequest.Features.extract_document_sentiment. # the text. "polarity": 3.14, # Polarity of the sentiment in the [-1.0, 1.0] range. Larger numbers # represent more positive sentiments. "magnitude": 3.14, # A non-negative number in the [0, +inf) range, which represents # the absolute magnitude of sentiment regardless of polarity (positive or # negative). }, "language": "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 field for more details. "sentences": [ # Sentences in the input document. Populated if the user enables # AnnotateTextRequest.Features.extract_syntax. { # Represents a sentence in the input document. "text": { # Represents an output piece of text. # The sentence text. "content": "A String", # The content of the output 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. }, }, ], }