Triple

T6121118
Position Surface form Disambiguated ID Type / Status
Subject Munhumutapa Building E136484 entity
Predicate locatedIn P40 FINISHED
Object Harare Province E252219 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: Harare Province | Statement: [Munhumutapa Building, locatedIn, Harare Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harare Province
Context triple: [Munhumutapa Building, locatedIn, Harare Province]
  • A. Harare Province chosen
    Harare Province is the metropolitan province in Zimbabwe that encompasses the capital city, Harare, and its surrounding urban areas.
  • B. Masvingo Province
    Masvingo Province is a region in southeastern Zimbabwe known for encompassing the historic Great Zimbabwe ruins and the city of Masvingo.
  • C. 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.
  • D. Mashonaland Central Province
    Mashonaland Central Province is a predominantly rural administrative region in northern Zimbabwe known for its agriculture and proximity to the capital, Harare.
  • E. Mashonaland West Province
    Mashonaland West Province is a region in northern Zimbabwe known for its rich agricultural lands, mineral resources, and wildlife areas along the Zambezi River.
  • 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_69c0089f851c81909e5e189a617dcff6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bf16ad48190958cc46510e02bd3 completed March 22, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135a5c428819090066ad785296736 completed March 23, 2026, 12:44 p.m.
Created at: March 22, 2026, 4:14 p.m.