Triple

T2045806
Position Surface form Disambiguated ID Type / Status
Subject Severstal Aircompany E45447 entity
Predicate headquartersLocation P62 FINISHED
Object Cherepovets E217616 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: Cherepovets | Statement: [Severstal Aircompany, headquartersLocation, Cherepovets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cherepovets
Context triple: [Severstal Aircompany, headquartersLocation, Cherepovets]
  • A. Cherepovets chosen
    Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
  • B. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • C. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • D. Elektrostal
    Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
  • E. Kaluga
    Kaluga is a historic city in western Russia known as a regional administrative center and an important site in several Russian uprisings and military campaigns.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9728f688190939d7c4df524f9b4 completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2031a55148190a1b96af35d109259 completed March 12, 2026, 12:04 a.m.
Created at: March 4, 2026, 7:39 p.m.