Triple

T12525622
Position Surface form Disambiguated ID Type / Status
Subject Oral E299430 entity
Predicate connectedByRoadTo P11435 FINISHED
Object Atyrau E276148 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: Atyrau | Statement: [Oral, connectedByRoadTo, Atyrau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atyrau
Context triple: [Oral, connectedByRoadTo, Atyrau]
  • A. Atyrau chosen
    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.
  • B. Syktyvkar
    Syktyvkar is the capital city of the Komi Republic in northwestern Russia, known as an administrative, cultural, and economic center of the region.
  • C. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • D. Kokshetau
    Kokshetau is a city in northern Kazakhstan that serves as the administrative and economic center of the surrounding Akmola Region.
  • E. Temirtau
    Temirtau is a major industrial city in Kazakhstan, best known for its large steel production complex and heavy metallurgical 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545d7e6c819080c3a85c18caa1ae completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb63c80048190be87b41cdd4ac775 completed May 7, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:57 p.m.