Triple

T12975845
Position Surface form Disambiguated ID Type / Status
Subject Vinci SA E321520 entity
Predicate hasSubsidiary P254 FINISHED
Object Cegelec E910092 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: Cegelec | Statement: [Vinci SA, hasSubsidiary, Cegelec]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cegelec
Context triple: [Vinci SA, hasSubsidiary, Cegelec]
  • A. Cegelec chosen
    Cegelec is an international engineering and technology services company specializing in electrical, automation, and information systems for infrastructure and industry.
  • B. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • C. Schneider Electric
    Schneider Electric is a French multinational company specializing in energy management and industrial automation solutions for homes, buildings, data centers, infrastructure, and industry.
  • D. Legrand
    Legrand is a French multinational company specializing in electrical and digital building infrastructure solutions, including switches, sockets, and cable management systems.
  • E. Tractebel Energia
    Tractebel Energia is a Brazilian electric power generation company known for operating large hydroelectric facilities and other energy assets across the country.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e48c0208190bb7ec80780480b37 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8ec821c81909398d8e02d69dcbf completed May 3, 2026, 2:54 a.m.
Created at: April 9, 2026, 8:37 p.m.