Triple

T19967287
Position Surface form Disambiguated ID Type / Status
Subject Hunyani River E479970 entity
Predicate majorRiverFor P165 FINISHED
Object Harare region NE NERFINISHED

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: Harare region | Statement: [Hunyani River, majorRiverFor, Harare region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harare region
Context triple: [Hunyani River, majorRiverFor, Harare region]
  • A. Harare Province chosen
    Harare Province is the metropolitan province in Zimbabwe that encompasses the capital city, Harare, and its surrounding urban areas.
  • B. Manicaland Province
    Manicaland Province is an eastern region of Zimbabwe known for its mountainous landscapes, rich mineral resources, and proximity to the border with Mozambique.
  • C. Mashonaland region
    Mashonaland region is a historical and agricultural region in northern Zimbabwe that includes the capital city, Harare, and is a key center of the country’s population and political life.
  • D. Masvingo Province
    Masvingo Province is a region in southeastern Zimbabwe known for encompassing the historic Great Zimbabwe ruins and the city of Masvingo.
  • E. Chiredzi District
    Chiredzi District is a rural district in southeastern Zimbabwe known for its sugarcane plantations and proximity to major wildlife conservation areas such as Gonarezhou National Park.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e523c19881909f9197037200dde6 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65bc5e41881908c1e8867820f1c0c completed April 20, 2026, 5 p.m.
Created at: April 10, 2026, 1:54 p.m.