Triple

T11095772
Position Surface form Disambiguated ID Type / Status
Subject Government of Nauru E262373 entity
Predicate seatOfGovernment P761 FINISHED
Object Yaren District E171595 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: Yaren District | Statement: [Government of Nauru, seatOfGovernment, Yaren District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yaren District
Context triple: [Government of Nauru, seatOfGovernment, Yaren District]
  • A. Yaren District chosen
    Yaren District is the de facto capital and main administrative center of the Pacific island nation of Nauru.
  • B. Atabey District
    Atabey District is an administrative district in Turkey’s Isparta Province, known as the birthplace of former Turkish President Süleyman Demirel.
  • C. Siyazan District
    Siyazan District is an administrative region in northeastern Azerbaijan known for its location along the Caspian Sea coast and its role in the country’s oil and agricultural sectors.
  • D. Bornova district
    Bornova district is a populous urban area and important residential, commercial, and educational hub within the city of İzmir, Turkey.
  • E. Bayanzürkh District
    Bayanzürkh District is one of the central administrative districts of Ulaanbaatar, Mongolia, known for its dense residential areas and growing commercial zones.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a0897188190b6c293b44990b3d4 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d69c8b4819092614e83e855430e completed April 19, 2026, 1:18 a.m.
Created at: April 8, 2026, 9:27 p.m.