Triple

T14303330
Position Surface form Disambiguated ID Type / Status
Subject Orenburg E354624 entity
Predicate partOf P40 FINISHED
Object Orenburg metropolitan area E354624 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: Orenburg metropolitan area | Statement: [Orenburg, partOf, Orenburg metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orenburg metropolitan area
Context triple: [Orenburg, partOf, Orenburg metropolitan area]
  • A. Orenburg chosen
    Orenburg is a major city in southwestern Russia near the Ural River, historically significant as a frontier fortress and administrative center linking European Russia with Central Asia.
  • B. Almetyevsk
    Almetyevsk is an industrial city in the Republic of Tatarstan, Russia, known especially as a major center of the country’s oil industry.
  • C. Cheboksary
    Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
  • D. Stavropol Upland
    Stavropol Upland is a hilly elevated region in southwestern Russia known for its fertile soils and significant role in the agriculture and landscape of Stavropol Krai.
  • E. Novokuybyshevsk
    Novokuybyshevsk is an industrial city in Samara Oblast, Russia, known for its major oil refining and petrochemical industries.
  • 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_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de717fc2348190bb6ba3109bd2871f completed April 14, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d2883e081909c53170ef30b4125 completed May 8, 2026, 1:32 a.m.
Created at: April 10, 2026, 1:12 a.m.