Triple

T10504856
Position Surface form Disambiguated ID Type / Status
Subject Chikomba District E247759 entity
Predicate hasServiceCenter P38419 FINISHED
Object Chivhu E867450 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: Chivhu | Statement: [Chikomba District, hasServiceCenter, Chivhu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chivhu
Context triple: [Chikomba District, hasServiceCenter, Chivhu]
  • A. Chivhu chosen
    Chivhu is a small town in central Zimbabwe known as an agricultural and commercial center along the main road between Harare and Masvingo.
  • B. Chivi
    Chivi is a rural district and settlement in southern Zimbabwe known for its communal farming communities and semi-arid landscape within Masvingo Province.
  • C. Chingola
    Chingola is a mining town in Zambia’s Copperbelt Province, known for its large copper mines and role in the country’s mining industry.
  • D. Tshiguvhu
    Tshiguvhu is a regional dialect of the Tshivenda language spoken by Venda communities in parts of South Africa.
  • E. Chavuma
    Chavuma is a small town in northwestern Zambia near the Angolan border, known for its proximity to the Zambezi River and scenic waterfalls.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5099f4dec8190a9851739c8bc9a69 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d99884c70481909fb45b7598f84c64 completed April 11, 2026, 12:40 a.m.
Created at: April 6, 2026, 12:26 p.m.