type: com.google.api.codegen.samplegen.v1p2.SampleConfigProto
schema_version: 1.2.0
samples:
- region_tag: language_entity_sentiment_gcs
  title: Analyzing Entity Sentiment (GCS)
  description: Analyzing Entity Sentiment in text file stored in Cloud Storage
  service: google.cloud.language.v1.LanguageService
  rpc: AnalyzeEntitySentiment
  request:
  - field: document.gcs_content_uri
    value: gs://cloud-samples-data/language/entity-sentiment.txt
    comment: |
      Google Cloud Storage URI where the file content is located.
      e.g. gs://[Your Bucket]/[Path to File]
    input_parameter: gcs_content_uri
  - field: document.type
    value: PLAIN_TEXT
    comment: "Available types: PLAIN_TEXT, HTML"
  - field: document.language
    value: en
    comment: |
      Optional. If not specified, the language is automatically detected.
      For list of supported languages:
        https://cloud.google.com/natural-language/docs/languages
  - field: encoding_type
    value: UTF8
    comment: "Available values: NONE, UTF8, UTF16, UTF32"
  response:
  - comment: Loop through entitites returned from the API
  - loop:
      collection: $resp.entities
      variable: entity
      body:
      - print: ["Representative name for the entity: %s", entity.name]
      - comment: ["Get entity type, e.g. PERSON, LOCATION, ADDRESS, NUMBER, et al"]
      - print: ["Entity type: %s", entity.type]
      - comment: ["Get the salience score associated with the entity in the [0, 1.0] range"]
      - print: ["Salience score: %s", entity.salience]
      - comment: ["Get the aggregate sentiment expressed for this entity in the provided document."]
      - define: sentiment = entity.sentiment
      - print: ["Entity sentiment score: %s", sentiment.score]
      - print: ["Entity sentiment magnitude: %s", sentiment.magnitude]
      - comment:
        - |
            Loop over the metadata associated with entity. For many known entities,
            the metadata is a Wikipedia URL (wikipedia_url) and Knowledge Graph MID (mid).
            Some entity types may have additional metadata, e.g. ADDRESS entities
            may have metadata for the address street_name, postal_code, et al.
      - loop:
          map: entity.metadata
          key: metadata_name
          value: metadata_value
          body:
          - print: ["%s = %s", metadata_name, metadata_value]
      - comment:
        - |
            Loop over the mentions of this entity in the input document.
            The API currently supports proper noun mentions.
      - loop:
          collection: entity.mentions
          variable: mention
          body:
          - print: ["Mention text: %s", mention.text.content]
          - comment: ["Get the mention type, e.g. PROPER for proper noun"]
          - print: ["Mention type: %s", mention.type]
  - comment:
    - |
        Get 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.
  - print: ["Language of the text: %s", $resp.language]