# Google Cloud Natural Language API . documents

## Instance Methods

Finds named entities (currently finds proper names) in the text,

Analyzes the sentiment of the provided text.

A convenience method that provides all the features that analyzeSentiment,

### Method Details

`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.
            },
          },
        ],
      }