Triple

T15524147
Position Surface form Disambiguated ID Type / Status
Subject SZFO E369039 entity
Predicate hasMajorCity P316 FINISHED
Object Syktyvkar E309974 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: Syktyvkar | Statement: [SZFO, hasMajorCity, Syktyvkar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Syktyvkar
Context triple: [SZFO, hasMajorCity, Syktyvkar]
  • A. Syktyvkar chosen
    Syktyvkar is the capital city of the Komi Republic in northwestern Russia, known as an administrative, cultural, and economic center of the region.
  • B. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • C. Kokshetau
    Kokshetau is a city in northern Kazakhstan that serves as the administrative and economic center of the surrounding Akmola 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. Atyrau
    Atyrau is a city in western Kazakhstan located near the Caspian Sea, notable for straddling the boundary between Europe and Asia and serving as a major center for the country’s oil industry.
  • 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_69d85a1794cc8190b0b428716296e63e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e04143bda08190a2dee44918c1ad1c completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d5706948190a1c0f466f7ef8857 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:05 a.m.