Google Cloud Natural Language API . documents

Instance Methods

analyzeEntities(body, x__xgafv=None)

Finds named entities (currently proper names and common nouns) in the text

analyzeSentiment(body, x__xgafv=None)

Analyzes the sentiment of the provided text.

analyzeSyntax(body, x__xgafv=None)

Analyzes the syntax of the text and provides sentence boundaries and

annotateText(body, x__xgafv=None)

A convenience method that provides all the features that analyzeSentiment,

Method Details

analyzeEntities(body, x__xgafv=None)
Finds named entities (currently proper names and common nouns) in the text
along with 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.
    "encodingType": "A String", # The encoding type used by the API to calculate offsets.
    "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.
# [Language Support](/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. "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. }, } 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. "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. }, "type": "A String", # The type of the entity mention. }, ], "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. "type": "A String", # The entity type. "name": "A String", # The representative name for the entity. "metadata": { # Metadata associated with the entity. # # Currently, Wikipedia URLs and Knowledge Graph MIDs are provided, if # available. The associated keys are "wikipedia_url" and "mid", respectively. "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.
    "encodingType": "A String", # The encoding type used by the API to calculate sentence offsets.
    "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.
# [Language Support](/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. "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. }, } 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. "score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 # (positive 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). }, "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": [ # The sentiment for all the sentences in the document. { # 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. }, "sentiment": { # Represents the feeling associated with the entire text or entities in # For calls to AnalyzeSentiment or if # AnnotateTextRequest.Features.extract_document_sentiment is set to # true, this field will contain the sentiment for the sentence. # the text. "score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 # (positive 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). }, }, ], }
analyzeSyntax(body, x__xgafv=None)
Analyzes the syntax of the text and provides sentence boundaries and
tokenization along with part of speech tags, dependency trees, and other
properties.

Args:
  body: object, The request body. (required)
    The object takes the form of:

{ # The syntax analysis request message.
    "encodingType": "A String", # The encoding type used by the API to calculate offsets.
    "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.
# [Language Support](/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. "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. }, } x__xgafv: string, V1 error format. Allowed values 1 - v1 error format 2 - v2 error format Returns: An object of the form: { # The syntax analysis response message. "tokens": [ # Tokens, along with their syntactic information, in the input document. { # 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. (For more # Dependency tree parse for this token. # information on dependency labels, see # http://www.aclweb.org/anthology/P13-2017 "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 # Parts of speech tag for this token. # are as defined in # http://www.lrec-conf.org/proceedings/lrec2012/pdf/274_Paper.pdf "case": "A String", # The grammatical case. "reciprocity": "A String", # The grammatical reciprocity. "mood": "A String", # The grammatical mood. "form": "A String", # The grammatical form. "gender": "A String", # The grammatical gender. "number": "A String", # The grammatical number. "person": "A String", # The grammatical person. "tag": "A String", # The part of speech tag. "tense": "A String", # The grammatical tense. "aspect": "A String", # The grammatical aspect. "proper": "A String", # The grammatical properness. "voice": "A String", # The grammatical voice. }, "lemma": "A String", # [Lemma](https://en.wikipedia.org/wiki/Lemma_%28morphology%29) of the token. }, ], "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. { # 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. }, "sentiment": { # Represents the feeling associated with the entire text or entities in # For calls to AnalyzeSentiment or if # AnnotateTextRequest.Features.extract_document_sentiment is set to # true, this field will contain the sentiment for the sentence. # the text. "score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 # (positive 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). }, }, ], }
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.
    "encodingType": "A String", # The encoding type used by the API to calculate offsets.
    "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.
# [Language Support](/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. "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. }, "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. "extractDocumentSentiment": True or False, # Extract document-level sentiment. "extractEntities": True or False, # Extract entities. "extractSyntax": True or False, # Extract syntax information. }, } 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. (For more # Dependency tree parse for this token. # information on dependency labels, see # http://www.aclweb.org/anthology/P13-2017 "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 # Parts of speech tag for this token. # are as defined in # http://www.lrec-conf.org/proceedings/lrec2012/pdf/274_Paper.pdf "case": "A String", # The grammatical case. "reciprocity": "A String", # The grammatical reciprocity. "mood": "A String", # The grammatical mood. "form": "A String", # The grammatical form. "gender": "A String", # The grammatical gender. "number": "A String", # The grammatical number. "person": "A String", # The grammatical person. "tag": "A String", # The part of speech tag. "tense": "A String", # The grammatical tense. "aspect": "A String", # The grammatical aspect. "proper": "A String", # The grammatical properness. "voice": "A String", # The grammatical voice. }, "lemma": "A String", # [Lemma](https://en.wikipedia.org/wiki/Lemma_%28morphology%29) 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. "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. }, "type": "A String", # The type of the entity mention. }, ], "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. "type": "A String", # The entity type. "name": "A String", # The representative name for the entity. "metadata": { # Metadata associated with the entity. # # Currently, Wikipedia URLs and Knowledge Graph MIDs are provided, if # available. The associated keys are "wikipedia_url" and "mid", respectively. "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. "score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 # (positive 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). }, "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. }, "sentiment": { # Represents the feeling associated with the entire text or entities in # For calls to AnalyzeSentiment or if # AnnotateTextRequest.Features.extract_document_sentiment is set to # true, this field will contain the sentiment for the sentence. # the text. "score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 # (positive 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). }, }, ], }