Triple

T2775049
Position Surface form Disambiguated ID Type / Status
Subject Samara Oblast E61547 entity
Predicate hasIndustrialCenter P3436 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: [Samara Oblast, hasIndustrialCenter, Tolyatti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tolyatti
Context triple: [Samara Oblast, hasIndustrialCenter, 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_69ab4b7cd13481909174bca9809ed259 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd7f9570819087f1b1cb59d68586 completed March 7, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f501e588190b666141f7e5ed6ae completed March 20, 2026, 5:09 p.m.
Created at: March 6, 2026, 9:57 p.m.