Triple

T4037885
Position Surface form Disambiguated ID Type / Status
Subject Volga Federal District E83870 entity
Predicate hasImportantCity P316 FINISHED
Object Cheboksary E407574 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: Cheboksary | Statement: [Volga Federal District, hasImportantCity, Cheboksary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheboksary
Context triple: [Volga Federal District, hasImportantCity, Cheboksary]
  • A. Cheboksary chosen
    Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
  • B. Orenburg
    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.
  • C. Naberezhnye Chelny
    Naberezhnye Chelny is a major industrial city in Russia’s Republic of Tatarstan, best known as the home of the KamAZ truck manufacturing plant.
  • D. Ufa
    Ufa is the capital and largest city of the Republic of Bashkortostan in Russia, known as a major industrial, cultural, and economic center in the Ural region.
  • E. Elista
    Elista is the capital city of the Republic of Kalmykia in Russia, known as a cultural and administrative center of the Kalmyk people and for its prominent Buddhist temples and chess-themed landmarks.
  • 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_69bf185bce7c8190ad94ab3f848a0040 completed March 21, 2026, 10:14 p.m.
Created at: March 9, 2026, 3:37 p.m.