Triple

T2581790
Position Surface form Disambiguated ID Type / Status
Subject Volga region E57107 entity
Predicate hasMajorCity P316 FINISHED
Object Tolyatti E376949 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: Tolyatti | Statement: [Volga region, hasMajorCity, Tolyatti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tolyatti
Context triple: [Volga region, hasMajorCity, Tolyatti]
  • A. Tolyatti chosen
    Tolyatti is a major industrial city in Russia on the Volga River, best known as the home of the AvtoVAZ automobile plant that produces Lada cars.
  • B. Ulyanovsk
    Ulyanovsk is a city in western Russia on the Volga River, best known as the birthplace of Vladimir Lenin and an important regional industrial and cultural center.
  • C. Penza
    Penza is a city in western Russia known as a regional cultural and industrial center.
  • D. Saratov
    Saratov is a major city in southwestern Russia known as an important cultural, educational, and industrial center on the banks of the Volga River.
  • E. Magnitogorsk
    Magnitogorsk is a major industrial city in Russia’s Chelyabinsk Oblast, historically centered around one of the world’s largest iron and steel works.
  • 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_69ab4a4dca6481908c301f8e317396e7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3c843bc8190837cea3441bf3ca1 completed March 7, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5335421348190a18cb74cdd885c82 completed March 14, 2026, 10:07 a.m.
Created at: March 6, 2026, 9:49 p.m.