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

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", "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", "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": 0.0700000002980232,
      "neutral": 0.170000001788139,
      "novelty": "string",
      "polarity": 0.686666644636601,
      "positive": 0.769999980926514,
      "score": 2,
      "site": "domain.com",
      "site_type": "news",
      "sub_categories": [
        "string"
      ],
      "taxonomy_keywords": [
        "string"
      ],
      "title": "string",
      "translated_main_story": "string",
      "translated_title": "string"
    }
  ],
  "size": 1,
  "has_next": true,
  "count": 1,
  "search_after": "string"
}