Triple

T9972237
Position Surface form Disambiguated ID Type / Status
Subject Vysotsky skyscraper E196234 entity
Predicate region P40 FINISHED
Object Urals E47138 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: Urals | Statement: [Vysotsky skyscraper, region, Urals]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urals
Context triple: [Vysotsky skyscraper, region, Urals]
  • A. Ural
    Ural is a Russian automotive brand best known for its heavy-duty off-road trucks and military-grade utility vehicles.
  • B. Ural
    Ural is a Russian professional football club based in Yekaterinburg that competes in the Russian Premier League.
  • C. Ural Mountains chosen
    The Ural Mountains are a long mountain range in western Russia that traditionally marks the natural boundary between Europe and Asia.
  • D. Verkhnyaya Tura
    Verkhnyaya Tura is a small industrial town in Russia’s Ural region, located within Sverdlovsk Oblast and historically associated with metallurgy and mining.
  • E. Kavkaz
    Kavkaz is a Russian port on the eastern side of the Kerch Strait that serves as a key maritime transport and ferry hub between Russia and Crimea.
  • 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_69ca82eea2b88190a0e511d21a31f386 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb7bb03688190a3f4fc1988b8fafa completed April 2, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23dd3e47c819095fef68b9939ec19 completed April 5, 2026, 10:47 a.m.
Created at: March 30, 2026, 8:48 p.m.