Triple

T18763827
Position Surface form Disambiguated ID Type / Status
Subject Turbomeca E458842 entity
Predicate formerName P65 FINISHED
Object Turbomeca SA NE NERFINISHED

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: Turbomeca SA | Statement: [Turbomeca, formerName, Turbomeca SA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turbomeca SA
Context triple: [Turbomeca, formerName, Turbomeca SA]
  • A. Turbomeca chosen
    Turbomeca is a French aerospace company renowned for designing and producing small and medium gas turbine engines, particularly for helicopters and military aircraft.
  • B. Safran Aircraft Engines
    Safran Aircraft Engines is a major French aerospace company that designs, develops, and manufactures aircraft and rocket engines for civil and military applications worldwide.
  • C. The Safran Company
    The Safran Company is a film and television production company best known for producing major horror franchises such as The Conjuring series.
  • D. Snecma
    Snecma is a French aerospace engine manufacturer known for developing and producing aircraft and rocket propulsion systems, including engines for commercial airliners and military aircraft.
  • E. Pratt & Whitney
    Pratt & Whitney is a major American aerospace manufacturer best known for designing and producing aircraft engines for commercial, military, and general aviation markets.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d395dba0819087568404508590cb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e58d82297c81909f720e2637cec737 completed April 20, 2026, 2:20 a.m.
Created at: April 10, 2026, 11:52 a.m.