Triple

T15996986
Position Surface form Disambiguated ID Type / Status
Subject Krasnodar E387993 entity
Predicate formerName P65 FINISHED
Object Ekaterinodar E387993 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: Ekaterinodar | Statement: [Krasnodar, formerName, Ekaterinodar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ekaterinodar
Context triple: [Krasnodar, formerName, Ekaterinodar]
  • A. Ekaterinodar chosen
    Ekaterinodar, now known as Krasnodar, was a major city in southern Russia that served as an important political and military center in the Kuban region.
  • B. Kirovabad
    Kirovabad was the Soviet-era name of the Azerbaijani city now known as Ganja, an important industrial and cultural center in western Azerbaijan.
  • C. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • D. Kirov
    Kirov is a town in Kaluga Oblast, Russia, known as a local administrative and industrial center.
  • E. Kirov
    Kirov is a Soviet nuclear-powered guided-missile battlecruiser that served as the lead ship of one of the largest and most heavily armed surface combatant classes built since World War II.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157882ef0819081143e530bd6413c completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b31b3b4819095d0c24ee471e2a9 completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 4:55 a.m.