Triple

T2945881
Position Surface form Disambiguated ID Type / Status
Subject Vologda Oblast E79498 entity
Predicate contains P35 FINISHED
Object city of 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: city of Cherepovets | Statement: [Vologda Oblast, contains, city of Cherepovets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Cherepovets
Context triple: [Vologda Oblast, contains, city of Cherepovets]
  • A. Cherepovets chosen
    Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
  • B. city of Rostov
    The city of Rostov is one of Russia’s oldest historic towns, renowned for its well-preserved kremlin and significant role in the cultural heritage of the Golden Ring region.
  • C. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • D. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • E. Tomsk
    Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
  • 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_69ad8b1089588190b74d9e2505e45762 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98b3f86c819094526c2af611bfb5 completed March 8, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b08692105c81908a3a146376b7417f completed March 10, 2026, 9:01 p.m.
Created at: March 8, 2026, 2:56 p.m.