Triple

T12475098
Position Surface form Disambiguated ID Type / Status
Subject MAKS Air Show E298155 entity
Predicate locatedIn P40 FINISHED
Object Zhukovsky E61661 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: Zhukovsky | Statement: [MAKS Air Show, locatedIn, Zhukovsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhukovsky
Context triple: [MAKS Air Show, locatedIn, Zhukovsky]
  • A. Zhukovsky chosen
    Zhukovsky is a town near Moscow, Russia, known as a major center of aviation research and industry.
  • B. Vasily Zhukovsky
    Vasily Zhukovsky was a prominent Russian Romantic poet and translator, best known for his ballads and for shaping early 19th-century Russian literature while serving as a tutor to the future Tsar Alexander II.
  • C. Anton Delvig
    Anton Delvig was a Russian poet, journalist, and close contemporary of Alexander Pushkin, known for his contributions to early 19th-century Russian literature and literary circles.
  • D. Apollon Maykov
    Apollon Maykov was a 19th-century Russian poet known for his classical style, historical and folkloric themes, and connections to the radical intellectual circles of his time.
  • E. Afanasy Fet
    Afanasy Fet was a 19th-century Russian lyric poet renowned for his musical, impressionistic verse and focus on nature and emotion.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcb194c81908b5e0320ddfd463c completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f25462881908dccb831b474875d completed May 2, 2026, 6:15 p.m.
Created at: April 8, 2026, 9:56 p.m.