Triple

T7315438
Position Surface form Disambiguated ID Type / Status
Subject Dalkia E168398 entity
Predicate hasSubsidiary P254 FINISHED
Object Dalkia Česká republika E168398 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: Dalkia Česká republika | Statement: [Dalkia, hasSubsidiary, Dalkia Česká republika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dalkia Česká republika
Context triple: [Dalkia, hasSubsidiary, Dalkia Česká republika]
  • A. Dalkia chosen
    Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
  • 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. Energodar
    Energodar is a Ukrainian city best known for hosting the Zaporizhzhia Nuclear Power Plant, the largest nuclear power station in Europe.
  • D. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • E. Gazpromavia
    Gazpromavia is a Russian airline owned by the energy company Gazprom, operating passenger and cargo flights as well as corporate and charter services, particularly in support of the oil and gas 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_69c68a5251508190ad68df4151cfeb04 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6ec04bdfc819093556aa5fa69e0e1 completed March 27, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e570bb0c8190a34c763e23e0b9da completed March 28, 2026, 2:28 p.m.
Created at: March 27, 2026, 3:02 p.m.