Triple
T13054247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chipinge District |
E327527
|
entity |
| Predicate | languageSpoken |
P151
|
FINISHED |
| Object | Ndau |
E147443
|
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: Ndau | Statement: [Chipinge District, languageSpoken, Ndau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ndau Context triple: [Chipinge District, languageSpoken, Ndau]
-
A.
Ndau
chosen
Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
-
B.
Nkoya
Nkoya is a Bantu language spoken primarily in western Zambia by the Nkoya people.
-
C.
Mpongwe
Mpongwe is a Bantu language variety spoken primarily in Gabon, recognized as one of the main dialects of the Myene language cluster.
-
D.
Nyakyusa
The Nyakyusa are a Bantu-speaking ethnic group primarily inhabiting the northern shores of Lake Malawi in southern Tanzania, known for their intensive agriculture and distinctive age-village social system.
-
E.
Inibaloi
Inibaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in Benguet province on Luzon.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980bb52d88190b5be12000e27a2c9 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbdead348190aa7aaa29c371d72a |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:58 p.m.