Triple
T14158149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macua |
E350865
|
entity |
| Predicate | hasDialect |
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: [Macua, hasDialect, Makhuwa-Marrevone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makhuwa-Marrevone Context triple: [Macua, hasDialect, Makhuwa-Marrevone]
-
A.
Makhuwa
chosen
Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
-
B.
Mazvihwa
Mazvihwa is a rural area in central Zimbabwe known for its communal lands and traditional Shona communities.
-
C.
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.
-
D.
Lanseria
Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
-
E.
Chivhu
Chivhu is a small town in central Zimbabwe known as an agricultural and commercial center along the main road between Harare and Masvingo.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61377de48190a3470d28f0edd34a |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd2804956c81909409fba998a87866 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 12:58 a.m.