Triple
T1337436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shona |
E28785
|
entity |
| Predicate | hasDialects |
P4251
|
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: [Shona, hasDialects, Ndau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ndau Context triple: [Shona, hasDialects, Ndau]
-
A.
Ndau
chosen
Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
-
B.
Ndowe
Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
-
C.
Nyanda
Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
-
D.
Ngoni
Ngoni is a Bantu language spoken by the Ngoni people of parts of Malawi, Tanzania, Mozambique, and Zambia, reflecting historical migrations from the Zulu region.
-
E.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1edda1c81909a1149b254b0d57e |
completed | March 1, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acde12d0dc81908a09c0221b8db3f6 |
completed | March 8, 2026, 2:25 a.m. |
Created at: March 1, 2026, 7:55 p.m.