Triple

T6212466
Position Surface form Disambiguated ID Type / Status
Subject Gatchina E138901 entity
Predicate regionCapitalOf P204 FINISHED
Object Gatchina urban settlement E138901 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: Gatchina urban settlement | Statement: [Gatchina, regionCapitalOf, Gatchina urban settlement]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gatchina urban settlement
Context triple: [Gatchina, regionCapitalOf, Gatchina urban settlement]
  • A. Gatchina chosen
    Gatchina is a historic Russian town near Saint Petersburg, known for its imperial palace complex and long association with the Romanov dynasty.
  • B. Voskresensk Urban Settlement
    Voskresensk Urban Settlement is a municipal formation in Russia that administers the town of Voskresensk and possibly surrounding localities within its jurisdiction.
  • C. Nikolskoye
    Nikolskoye is a town in northwestern Russia known as part of the Saint Petersburg metropolitan area in Leningrad Oblast.
  • D. Nikolskoye
    Nikolskoye is the main and only permanent settlement on Russia’s remote Commander Islands in the Bering Sea.
  • E. city of Poshekhonye
    The city of Poshekhonye is a small historic town in central Russia known for its traditional cheese production and location along the Sogozha River.
  • 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_69c008ada364819096c9e92c74d639b5 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0628c52ec8190b9c62c7fdc0aa83b completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20da55e3c81909a61471b38e88894 completed March 24, 2026, 4:05 a.m.
Created at: March 22, 2026, 4:21 p.m.