Triple

T16978582
Position Surface form Disambiguated ID Type / Status
Subject Mwenezi E411880 entity
Predicate waterSource P4102 FINISHED
Object Mwenezi River 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: Mwenezi River | Statement: [Mwenezi, waterSource, Mwenezi River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mwenezi River
Context triple: [Mwenezi, waterSource, Mwenezi River]
  • A. Mwenezi River chosen
    The Mwenezi River is a significant river in southern Africa that flows through Zimbabwe and Mozambique, supporting local agriculture, wildlife, and communities along its course.
  • B. Usutu River
    The Usutu River is a major river in southern Africa that flows through South Africa, Eswatini, and Mozambique before emptying into the Indian Ocean.
  • C. Unya River
    The Unya River is a waterway in northwestern Russia that feeds into the larger Pechora River system.
  • D. Lukusuzi River
    The Lukusuzi River is a watercourse in eastern Zambia that forms a natural boundary and key ecological feature of Lukusuzi National Park.
  • E. Busira River
    The Busira River is a major waterway in the Democratic Republic of the Congo that forms part of the central Congo River basin and drains extensive areas of tropical rainforest.
  • 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.