Triple

T16871679
Position Surface form Disambiguated ID Type / Status
Subject Sergey Dvortsevoy E421182 entity
Predicate placeOfBirth P1 FINISHED
Object Shymkent E51721 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: Shymkent | Statement: [Sergey Dvortsevoy, placeOfBirth, Shymkent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shymkent
Context triple: [Sergey Dvortsevoy, placeOfBirth, Shymkent]
  • A. Shymkent chosen
    Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
  • B. Kokshetau
    Kokshetau is a city in northern Kazakhstan that serves as the administrative and economic center of the surrounding Akmola Region.
  • C. Zhezkazgan
    Zhezkazgan is a major industrial and mining city in central Kazakhstan, known especially for its large copper deposits and metallurgical complex.
  • D. Temirtau
    Temirtau is a major industrial city in Kazakhstan, best known for its large steel production complex and heavy metallurgical industry.
  • E. Almaty
    Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
  • 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3b7f31b448190a21e3e4d1a0d2f73 completed April 18, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2b0dcbc8190a164cbd57586ac9c completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 5:29 a.m.