Triple

T17295545
Position Surface form Disambiguated ID Type / Status
Subject Chelyabinsk Oblast E419900 entity
Predicate hasCity P316 FINISHED
Object Magnitogorsk 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: Magnitogorsk | Statement: [Chelyabinsk Oblast, hasCity, Magnitogorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magnitogorsk
Context triple: [Chelyabinsk Oblast, hasCity, Magnitogorsk]
  • A. Magnitogorsk chosen
    Magnitogorsk is a major industrial city in Russia’s Chelyabinsk Oblast, historically centered around one of the world’s largest iron and steel works.
  • B. Nizhny Tagil
    Nizhny Tagil is a major industrial city in Russia’s Sverdlovsk Oblast, historically known for its metallurgical plants and role in the country’s heavy industry.
  • C. Nizhnekamsk
    Nizhnekamsk is a major industrial city in Russia known for its large petrochemical and oil refining complexes.
  • D. Lipetsk
    Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
  • E. Sverdlovsk
    Sverdlovsk is the former name of Yekaterinburg, a major industrial and cultural city in Russia’s Ural region.
  • 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e437875b208190bcf0df2ded546257 completed April 19, 2026, 2:01 a.m.
Created at: April 10, 2026, 5:40 a.m.