ESG
Universes

Universes ESG Documents

Get ESG documents for one universe

GET
https://api.textreveal.com/v3/universes/{universe_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

  • universe_id*uuid

    Unique identifier of the universe

  • 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

  • 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"]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"

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"
    }
  ],
  "size": 1,
  "has_next": true,
  "count": 1,
  "search_after": "string"
}