Triple

T4914101
Position Surface form Disambiguated ID Type / Status
Subject Serre-Ponçon Dam E110305 entity
Predicate ownedBy P347 FINISHED
Object Électricité de France E166775 NE FINISHED

How this triple was built (2 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: Électricité de France | Statement: [Serre-Ponçon Dam, ownedBy, Électricité de France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Électricité de France
Context triple: [Serre-Ponçon Dam, ownedBy, Électricité de France]
  • A. Électricité de France chosen
    Électricité de France is France’s state-owned electric utility company and one of the world’s largest producers and distributors of electricity, particularly known for its extensive nuclear power fleet.
  • 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. Areva
    Areva was a French multinational group specializing in nuclear power and renewable energy technologies, known for its involvement in the entire nuclear fuel cycle.
  • D. TotalEnergies
    TotalEnergies is a major French multinational energy company engaged in oil, gas, and renewable energy production and distribution worldwide.
  • E. Dalkia
    Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd44132b94819088522d92beaadc78 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e9f12b48190b3cb5378958d03cd completed March 20, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77a1ef488190ac9cc34e67a8b243 completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:29 p.m.