Triple

T7374106
Position Surface form Disambiguated ID Type / Status
Subject Suez E170080 entity
Predicate formerName P65 FINISHED
Object Suez Environnement
Suez Environnement was a French multinational company specializing in water and waste management services before being rebranded under the Suez name.
 E660626 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Suez Environnement | Statement: [Suez, formerName, Suez Environnement]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Suez Environnement
Context triple: [Suez, formerName, Suez Environnement]
  • A. Veolia Environnement
    Veolia Environnement is a French multinational company specializing in water, waste, and energy management services worldwide.
  • B. GDF Suez
    GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
  • C. Dalkia
    Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
  • D. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • E. Eiffage
    Eiffage is a major French construction and civil engineering company known for delivering large-scale infrastructure projects such as the Millau Viaduct.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Suez Environnement
Triple: [Suez, formerName, Suez Environnement]
Generated description
Suez Environnement was a French multinational company specializing in water and waste management services before being rebranded under the Suez name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Suez Environnement
Target entity description: Suez Environnement was a French multinational company specializing in water and waste management services before being rebranded under the Suez name.
  • A. Veolia Environnement
    Veolia Environnement is a French multinational company specializing in water, waste, and energy management services worldwide.
  • B. GDF Suez
    GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
  • C. Dalkia
    Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
  • D. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • E. Eiffage
    Eiffage is a major French construction and civil engineering company known for delivering large-scale infrastructure projects such as the Millau Viaduct.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1a6643c81909d626c8b6a7a11fd completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802ce8e408190946637d04083521c completed March 28, 2026, 4:33 p.m.
NEDg Description generation batch_69c80739a09c819096267cc415e3655e completed March 28, 2026, 4:52 p.m.
NED2 Entity disambiguation (via description) batch_69c80810aff481909f4ac43f72101eb7 completed March 28, 2026, 4:55 p.m.
Created at: March 27, 2026, 3:07 p.m.