Triple
T3904885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swazi people |
E90581
|
entity |
| Predicate | hasMonarch |
P765
|
FINISHED |
| Object | Ngwenyama |
E397184
|
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: Ngwenyama | Statement: [Swazi people, hasMonarch, Ngwenyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ngwenyama Context triple: [Swazi people, hasMonarch, Ngwenyama]
-
A.
Ngwenyama
chosen
Ngwenyama is the traditional Swazi royal title meaning "lion," used for the reigning king of Eswatini.
-
B.
Dawakin Kudu
Dawakin Kudu is a prominent town and local government area in northern Nigeria known for its role in agriculture and education within Kano State.
-
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.
Enyeama
Enyeama is a Nigerian surname most prominently associated with Vincent Enyeama, a renowned former goalkeeper and captain of the Nigeria national football team.
-
E.
Kwando
Kwando is a river in southern Africa that flows through Angola, Namibia, and Botswana, forming part of the region’s complex wetland and river system.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed0fb9888190add847806555a14a |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b528540ad48190ac86774c76a2ffd4 |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:22 p.m.