Triple

T4037886
Position Surface form Disambiguated ID Type / Status
Subject Volga Federal District E83870 entity
Predicate hasImportantCity P316 FINISHED
Object Orenburg 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 | Statement: [Volga Federal District, hasImportantCity, Orenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orenburg
Context triple: [Volga Federal District, hasImportantCity, Orenburg]
  • 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. Cheboksary
    Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
  • C. Kamyshin
    Kamyshin is a significant industrial and river port city on the Volga River in southwestern Russia.
  • D. Omsk
    Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
  • E. Astrakhan
    Astrakhan is a historic Russian city near the Caspian Sea, known as a key Volga River port and gateway to the Volga Delta region.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb3656f08190aa5286d951013646 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf2196e8e88190b8da71ecfb07dfc8 completed March 21, 2026, 10:54 p.m.
Created at: March 9, 2026, 3:37 p.m.