Triple

T6731150
Position Surface form Disambiguated ID Type / Status
Subject Manyika E153635 entity
Predicate spokenInRegion P7445 FINISHED
Object Mutare area 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 area | Statement: [Manyika, spokenInRegion, Mutare area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mutare area
Context triple: [Manyika, spokenInRegion, Mutare area]
  • 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. Marondera
    Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
  • C. Unawatuna
    Unawatuna is a popular coastal town in southern Sri Lanka known for its palm-fringed beach, coral-rich bay, and laid-back tourist atmosphere.
  • D. Mutare City Council
    Mutare City Council is the local municipal authority responsible for administering and providing public services in the city of Mutare, Zimbabwe.
  • E. Mpanda
    Mpanda is a town in western Tanzania that serves as an important administrative and commercial hub for the surrounding region.
  • 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_69c70b029960819090de37c99e80ceb9 completed March 27, 2026, 10:56 p.m.
Created at: March 27, 2026, 2:09 p.m.