Triple

T22325453
Position Surface form Disambiguated ID Type / Status
Subject Perm Governorate E551889 entity
Predicate includedCity P8465 FINISHED
Object Krasnokamsk NE NERFINISHED

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: Krasnokamsk | Statement: [Perm Governorate, includedCity, Krasnokamsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krasnokamsk
Context triple: [Perm Governorate, includedCity, Krasnokamsk]
  • A. Krasnokamsk chosen
    Krasnokamsk is an industrial city in western Russia known for its paper, printing, and chemical industries.
  • B. Krasnoturyinsk
    Krasnoturyinsk is an industrial town in Russia’s Ural region known for its mining and metallurgical industries.
  • C. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • D. Kastornoye
    Kastornoye is a locality in Russia historically notable as the namesake and focal area of the Voronezh–Kastornoye military offensive during World War II.
  • E. Kirzhach
    Kirzhach is a small historic town in western Russia known for its traditional architecture and location on the Kirzhach River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e482f788190b78d1588fc26d606 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15768696481909be124e86c23d551 completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:42 p.m.