ESG
Entities

Entities ESG Documents

Get ESG documents for one entity

GET
https://api.textreveal.com/v3/entities/{entity_id}/esg/documents

Each ESG document has a hidden reliability score which is calculated from multiple fields:

  • The domain of the url of the document
  • The sentiments (negative/positive)
  • The quality score of the document
  • If the source is of high authority (is_high_authority_source)

The higher the reliability score, the more relevant the document is. By default, the result is sorted by reliability score in descending order.

Request

Parameters

  • entity_id*uuid

    Unique identifier of the entity

  • sizeinteger

    Number of records per page

    Default: 10Range: [1, 1000]
  • search_afterstring

    search_after field value from the previous page

  • scoreinteger (operator)

    Intensity score

    You can input an integer or use the following operators: lt (<), lte (≤), gt (>), gte (≥), neq (≠), in, nin (not in), between

    Range: [1, 5]
  • extract_datedate (operator)

    Extraction date of the document

    You can input a date or use the following operators: lt (<), lte (≤), gt (>), gte (≥), neq (≠), between

    Example: "between:2022-01-01;2022-01-02"
  • case_iduuid[]

    Unique case identifier to retrieve the associated documents

    You can specify multiple values

  • event_iduuid[]

    Unique event identifier to retrieve the associated documents

    You can specify multiple values

  • categorystring (enum)

    Filter by category.

    Values: "E", "S", "G"
  • sub_category(string (enum))[]

    Filter by one or many sub_categories.

    Values: "Animal Welfare", "Atmospheric Pollution", "Biodiversity And Ecosystems", "Climate Change", "Energy & Natural Resources Management", "Environmental Misreporting", "Food Waste", "Industrial Accidents & Physical Risk", "Land And Soil Pollution", "Other Pollutions", "Waste Management", "Water Consumption", "Water Pollution", "Child Labor", "Community Health And Safety", "Customer Relations", "Diversity & Inclusion (Beyond The Workplace)", "Forced Labor", "Freedom Of Association And Collective Bargaining", "Fundamental Human Rights", "Occupational Health & Safety", "Rights Of Indigenous Communities", "Right To Property", "Social Misreporting", "Violation Of Human Rights In Conflict Or High Risk Zones", "Working Conditions", "Workplace Diversity & Inclusion", "Accounting And Securities Fraud", "Anti-Competitive Practices", "Board Of Directors & Senior Management", "Corruption And Bribery", "Csr Misreporting", "Data Privacy & Cyber Security", "Embezzlement", "Executive Pay", "Fraud", "Legal And Investigative Exposure", "Marketing & Communication", "Money Laundering", "Price Fixing", "Supply Chain", "Tax Strategy", "Terrorism Financing"
  • orderfield:direction[]

    Order to apply to the result.

    Possible fields are: reliability, extract_date, score.

    Possible directions are: asc and desc.

    You can specifiy multiples values.

    Default: [reliability:desc, extract_date:asc]Example: "reliability:desc"
  • fields(string (enum))[]

    Fields to include in the response

    Default: ["id", "categories", "case_id", "country", "datamarts_document_id", "entity_keywords", "entity_id", "event_id", "url", "extract_date", "dashboard_url", "language", "main_story", "negative", "neutral", "novelty", "polarity", "positive", "score", "site", "site_type", "sub_categories", "taxonomy_keywords", "title", "is_high_authority_source", "translated_main_story", "translated_title"]Values: "id", "categories", "case_id", "country", "datamarts_document_id", "entity_keywords", "entity_id", "event_id", "url", "extract_date", "dashboard_url", "language", "main_story", "negative", "neutral", "novelty", "polarity", "positive", "score", "site", "site_type", "sub_categories", "taxonomy_keywords", "title", "is_high_authority_source", "translated_main_story", "translated_title"
  • translatelanguage-code

    In which language to translate the results.

    Default translated fields are: title, main_story.

    If empty, translated_ fields won't be returned.

    Example: french

Response

Response - 200

Properties of the documents. Documents are ranked by source relevance, then `extract_date` and then `id`.

  • data*object[]

    Properties of the documents

  • size*integer

    Number of records per page requested.

    Example: 1
  • has_next*boolean

    True if there are more records available.

    Example: true
  • count*integer

    Number of records returned in the current page.

    Example: 1
  • search_after*string | null

    Cursor for next page.

Response
{
  "data": [
    {
      "id": "09210f4c-7283-45c9-9b7a-ce5cd6ec7ea6",
      "categories": [
        "E"
      ],
      "case_id": "5eb7182b-9b55-4f7a-b3e1-49062ee7cef9",
      "country": "fr",
      "datamarts_document_id": "string",
      "entity_keywords": [
        "string"
      ],
      "entity_id": "00000000-0000-0000-0000-000000000000",
      "event_id": "e7c2464e-0dc8-441a-970b-0d23eeabe3d1",
      "url": "https://domain.com/article#anchor",
      "extract_date": "2025-04-09T14:15:54.000Z",
      "dashboard_url": "https://dashboards.textreveal.com/controversy/09210f4c-7283-45c9-9b7a-ce5cd6ec7ea6",
      "language": "fre",
      "main_story": "string",
      "negative": 0.01,
      "neutral": 0.2,
      "novelty": "string",
      "polarity": 0.78765434,
      "positive": 0.8,
      "score": 2,
      "site": "domain.com",
      "site_type": "news",
      "sub_categories": [
        "Climate Change",
        "Water Pollution"
      ],
      "taxonomy_keywords": [
        "string"
      ],
      "title": "string",
      "is_high_authority_source": true,
      "translated_main_story": "string",
      "translated_title": "string"
    }
  ],
  "size": 1,
  "has_next": true,
  "count": 1,
  "search_after": "string"
}