Triple

T3356992
Position Surface form Disambiguated ID Type / Status
Subject Makhuwa E70628 entity
Predicate hasDialects P4251 FINISHED
Object Makhuwa-Marrevone E70628 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: Makhuwa-Marrevone | Statement: [Makhuwa, hasDialects, Makhuwa-Marrevone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makhuwa-Marrevone
Context triple: [Makhuwa, hasDialects, Makhuwa-Marrevone]
  • A. Makhuwa chosen
    Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
  • B. Soshanguve
    Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
  • C. Lanseria
    Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
  • D. Mazabuka
    Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
  • E. Mafadi
    Mafadi is a prominent mountain peak on the border of South Africa and Lesotho, renowned as the highest point in South Africa and a popular destination for serious hikers and mountaineers.
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb244435c81908e35d2aa36ec4f46 completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3342fed748190814da1b968015d43 completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:13 p.m.