Triple

T11182558
Position Surface form Disambiguated ID Type / Status
Subject Central Kazakhstan E264576 entity
Predicate hasMajorCity P316 FINISHED
Object Karaganda E52322 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: Karaganda | Statement: [Central Kazakhstan, hasMajorCity, Karaganda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karaganda
Context triple: [Central Kazakhstan, hasMajorCity, Karaganda]
  • A. Karaganda chosen
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • B. Kokshetau
    Kokshetau is a city in northern Kazakhstan that serves as the administrative and economic center of the surrounding Akmola Region.
  • C. Syktyvkar
    Syktyvkar is the capital city of the Komi Republic in northwestern Russia, known as an administrative, cultural, and economic center of the region.
  • D. Kaspiysk
    Kaspiysk is a coastal city on the Caspian Sea in the Republic of Dagestan, Russia, known for its industrial base and strategic naval facilities.
  • E. Yoshkar-Ola
    Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8a9c5e081908c85b41a268428fb completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af38e3548190a5192894932d9b1d completed May 3, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:29 p.m.