Triple

T8871288
Position Surface form Disambiguated ID Type / Status
Subject Cherkessk E211161 entity
Predicate formerName P65 FINISHED
Object Batalpashinsk E763439 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: Batalpashinsk | Statement: [Cherkessk, formerName, Batalpashinsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batalpashinsk
Context triple: [Cherkessk, formerName, Batalpashinsk]
  • A. Batalpashinskaya chosen
    Batalpashinskaya was the former name of the city now known as Cherkessk, a regional center in the North Caucasus of Russia.
  • B. Volnovakha
    Volnovakha is a town in eastern Ukraine that serves as an important local administrative and transport hub within Donetsk Oblast.
  • C. Baturyn
    Baturyn is a historic town in northern Ukraine that served as a major political and military center of the Cossack Hetmanate in the 17th–18th centuries.
  • D. Bogdanovka
    Bogdanovka is a village in Ukraine known as the site of a World War II massacre of Jews and now commemorated as a Holocaust memorial location.
  • E. Kozelsk
    Kozelsk is a historic town in western Russia known for its medieval defenses and location within Kaluga Oblast.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6126d2f88190979ab25772ee657c completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfab9e87cc8190ae3c8c683aa0921e completed April 3, 2026, 11:59 a.m.
Created at: March 30, 2026, 6:51 p.m.