Triple

T15970511
Position Surface form Disambiguated ID Type / Status
Subject Lake Chivero E387307 entity
Predicate suppliesWaterTo P4102 FINISHED
Object Chitungwiza E881519 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: Chitungwiza | Statement: [Lake Chivero, suppliesWaterTo, Chitungwiza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chitungwiza
Context triple: [Lake Chivero, suppliesWaterTo, Chitungwiza]
  • A. Chitungwiza chosen
    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.
  • B. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • C. Harare
    Harare is the largest city and main economic, political, and cultural center of Zimbabwe.
  • D. Chegutu
    Chegutu is a town in central northern Zimbabwe known for its agricultural activities and gold mining.
  • E. 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.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157291214819088d65e984609e42c completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fffee76e9481908e74c32cb8263875 completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 4:54 a.m.