Triple

T6731182
Position Surface form Disambiguated ID Type / Status
Subject Korekore E153636 entity
Predicate region P40 FINISHED
Object Mashonaland E47508 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: Mashonaland | Statement: [Korekore, region, Mashonaland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mashonaland
Context triple: [Korekore, region, Mashonaland]
  • A. Mashonaland region chosen
    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.
  • B. 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.
  • C. Matabeleland
    Matabeleland is a historical region in southwestern Zimbabwe, traditionally inhabited by the Ndebele people and centered around the city of Bulawayo.
  • D. 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.
  • E. 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.
  • 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_69c6880bdd68819097de8b6099992682 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d16a30888190ae474d90bb71ac49 completed March 27, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ad6644f4819080db0a3981470d96 completed March 28, 2026, 10:28 a.m.
Created at: March 27, 2026, 2:09 p.m.