Triple

T16061588
Position Surface form Disambiguated ID Type / Status
Subject SkyTeam E389626 entity
Predicate hasMember P10 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: [SkyTeam, hasMember, Aeroflot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aeroflot
Context triple: [SkyTeam, hasMember, 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183795100819097be92e6d07dc5b1 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbe88a608190bc0a0cbfdb71e81d completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:57 a.m.