Triple

T12914380
Position Surface form Disambiguated ID Type / Status
Subject Mil Mi-6 E308937 entity
Predicate usedBy P260 FINISHED
Object Aeroflot E18861 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: Aeroflot | Statement: [Mil Mi-6, usedBy, Aeroflot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aeroflot
Context triple: [Mil Mi-6, usedBy, Aeroflot]
  • A. Aeroflot chosen
    Aeroflot is Russia's largest and flag-carrying airline, headquartered in Moscow and operating an extensive network of domestic and international flights.
  • B. Rossiya Airlines
    Rossiya Airlines is a Russian airline based in Saint Petersburg that operates domestic and international passenger flights as part of the Aeroflot Group.
  • C. Ural Airlines
    Ural Airlines is a Russian airline based in Yekaterinburg that operates domestic and international passenger flights across Europe, Asia, and the Middle East.
  • D. Aerosvit Airlines
    Aerosvit Airlines was a now-defunct Ukrainian carrier that operated domestic and international flights, primarily from its main base in Kyiv.
  • E. Arkhangelsk Airlines
    Arkhangelsk Airlines was a Russian regional airline based in Arkhangelsk that later became known as Nordavia.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971a0d6508190bca9668e9e06abfe completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a56ea03c819093a5b8657e27768e completed May 3, 2026, 1:31 a.m.
Created at: April 9, 2026, 5:41 p.m.