Triple

T16978621
Position Surface form Disambiguated ID Type / Status
Subject Masvingo–Mutare road E411882 entity
Predicate servesCity P82 FINISHED
Object Masvingo 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: Masvingo | Statement: [Masvingo–Mutare road, servesCity, Masvingo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masvingo
Context triple: [Masvingo–Mutare road, servesCity, Masvingo]
  • A. Masvingo chosen
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • B. 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.
  • C. Harare
    Harare is the largest city and main economic, political, and cultural center of Zimbabwe.
  • D. Nsanje
    Nsanje is a town in southern Malawi near the border with Mozambique, known as a key transport and trading center in the Lower Shire Valley.
  • E. Mutare
    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.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d185a9408190a991bf8a1ef694f0 completed April 18, 2026, 6:46 p.m.
Created at: April 10, 2026, 5:32 a.m.