Triple

T13091101
Position Surface form Disambiguated ID Type / Status
Subject Kimrsky Uyezd E310463 entity
Predicate administrativeCentre P1474 FINISHED
Object Kimry E280198 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: Kimry | Statement: [Kimrsky Uyezd, administrativeCentre, Kimry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimry
Context triple: [Kimrsky Uyezd, administrativeCentre, Kimry]
  • A. Kimry chosen
    Kimry is a small Russian town on the Volga River known historically for its shoemaking industry and wooden architecture.
  • B. Vytegra
    Vytegra is a small town in northwestern Russia known as a regional center near Lake Onega and the White Sea–Baltic Canal.
  • C. Stockheim
    Stockheim is a village and district of the town of Brackenheim in the Heilbronn district of Baden-Württemberg, Germany.
  • D. Kezlev
    Kezlev is the historical Crimean Tatar name for the city now known as Eupatoria, a coastal town on the western shore of Crimea.
  • E. Dagomys
    Dagomys is a coastal resort settlement on the Black Sea in the Sochi area of Krasnodar Krai, Russia, known for its beaches and subtropical climate.
  • 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d9813acbac8190b2fe5e07287457cf completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27417308190b388be4a31ce4b5d completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 9:03 p.m.