Triple

T6118507
Position Surface form Disambiguated ID Type / Status
Subject Vaninsky District E136420 entity
Predicate administrativeCenter P1474 FINISHED
Object Vanino E25214 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: Vanino | Statement: [Vaninsky District, administrativeCenter, Vanino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vanino
Context triple: [Vaninsky District, administrativeCenter, Vanino]
  • A. Vanino chosen
    Vanino is a key port town in Russia’s Far East that serves as an important hub for maritime trade and transport in the region.
  • B. Togliatti
    Togliatti is a major industrial city in Russia best known as the home of the AvtoVAZ automobile plant that produces Lada cars.
  • C. del Vasto
    Del Vasto is an Italian surname historically associated with the noble family of Adelaide del Vasto, a prominent medieval countess and regent in Sicily.
  • D. Mozdok
    Mozdok is a town in the Republic of North Ossetia–Alania in southwestern Russia, known historically as a strategic military and trading outpost in the North Caucasus region.
  • E. San Savino
    San Savino is a small locality within the municipality of Predappio in the Emilia-Romagna region of northern Italy.
  • 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_69c0089f851c81909e5e189a617dcff6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bec9b8c8190b3268b0ba952aae6 completed March 22, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135a5c428819090066ad785296736 completed March 23, 2026, 12:44 p.m.
Created at: March 22, 2026, 4:14 p.m.