Triple

T13593604
Position Surface form Disambiguated ID Type / Status
Subject Mayor of Mutare E324756 entity
Predicate appliesToJurisdiction P82 FINISHED
Object Mutare E10728 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: Mutare | Statement: [Mayor of Mutare, appliesToJurisdiction, Mutare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mutare
Context triple: [Mayor of Mutare, appliesToJurisdiction, Mutare]
  • A. Mutare chosen
    Mutare is a major city in eastern Zimbabwe, serving as the capital of Manicaland Province and an important commercial and transport hub near the border with Mozambique.
  • B. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • C. Marondera
    Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
  • D. Chitungwiza
    Chitungwiza is a large high-density dormitory town in Zimbabwe situated just south of Harare, known for its rapid urban growth and vibrant informal economy.
  • E. Cedza
    Cedza is a Swazi prince and social entrepreneur known for his work in youth leadership and development initiatives.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb057f1c881909a3bb77c659a724a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce60b1248190addfbfc1c5ccd2d1 completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 9:49 p.m.