Triple

T11166922
Position Surface form Disambiguated ID Type / Status
Subject Yipunu E264182 entity
Predicate region P40 FINISHED
Object Nyanga Province E861663 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: Nyanga Province | Statement: [Yipunu, region, Nyanga Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyanga Province
Context triple: [Yipunu, region, Nyanga Province]
  • A. Nyanga Province chosen
    Nyanga Province is a sparsely populated, resource-rich administrative region in southern Gabon known for its forests, rivers, and coastal areas along the Atlantic Ocean.
  • B. Nyanga District
    Nyanga District is an administrative district in northeastern Zimbabwe known for its mountainous landscapes and popular tourist attractions such as Nyanga National Park.
  • C. Rakai District
    Rakai District is a rural administrative district in southern Uganda known for its agricultural economy and its early prominence in the country’s HIV/AIDS epidemic.
  • D. Shinyanga Region
    Shinyanga Region is an administrative region in northwestern Tanzania known for its agriculture, mining activities, and proximity to Lake Victoria.
  • E. Nyando District
    Nyando District was a former administrative district in Kenya’s Nyanza Province, located in the western part of the country near Lake Victoria.
  • 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_69d7e88843cc81909e503f0921c6d297 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4aced563c8190a56ab5ff0618d21f completed April 19, 2026, 10:22 a.m.
Created at: April 8, 2026, 9:29 p.m.