Triple

T10711568
Position Surface form Disambiguated ID Type / Status
Subject ROSSIYA E252549 entity
Predicate callsignFor P1565 FINISHED
Object Rossiya Airlines E43256 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: Rossiya Airlines | Statement: [ROSSIYA, callsignFor, Rossiya Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rossiya Airlines
Context triple: [ROSSIYA, callsignFor, Rossiya Airlines]
  • A. Rossiya Airlines chosen
    Rossiya Airlines is a Russian airline based in Saint Petersburg that operates domestic and international passenger flights as part of the Aeroflot Group.
  • B. Aeroflot
    Aeroflot is Russia's largest and flag-carrying airline, headquartered in Moscow and operating an extensive network of domestic and international flights.
  • 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. Siberia Airlines
    Siberia Airlines, now known as S7 Airlines, is a major Russian airline that operates domestic and international flights with a primary hub in Novosibirsk.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe523de08190a82c8f057fe8baf6 completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbb70f67c88190980f362fcea9d800 completed April 12, 2026, 3:15 p.m.
Created at: April 8, 2026, 9:13 p.m.