Triple
T11457327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Cedza Dlamini |
E271563
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Cedza
Cedza is a Swazi prince and social entrepreneur known for his work in youth leadership and development initiatives.
|
E925684
|
NE FINISHED |
How this triple was built (4 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: Cedza | Statement: [Prince Cedza Dlamini, givenName, Cedza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cedza Context triple: [Prince Cedza Dlamini, givenName, Cedza]
-
A.
Chinhoyi
Chinhoyi is a town in northern Zimbabwe known as an administrative center and for the nearby Chinhoyi Caves.
-
B.
Marondera
Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
-
C.
Sinazongwe
Sinazongwe is a lakeside town in southern Zambia situated on the shores of Lake Kariba, known primarily for fishing and agriculture.
-
D.
Chiredzi
Chiredzi is a town in southeastern Zimbabwe known as a center for sugarcane farming and a gateway to nearby wildlife and conservation areas.
-
E.
Zvimba
Zvimba is a town in northern Zimbabwe located within Mashonaland West Province, known primarily as a rural administrative and farming center.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cedza Triple: [Prince Cedza Dlamini, givenName, Cedza]
Generated description
Cedza is a Swazi prince and social entrepreneur known for his work in youth leadership and development initiatives.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cedza Target entity description: Cedza is a Swazi prince and social entrepreneur known for his work in youth leadership and development initiatives.
-
A.
Chinhoyi
Chinhoyi is a town in northern Zimbabwe known as an administrative center and for the nearby Chinhoyi Caves.
-
B.
Marondera
Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
-
C.
Sinazongwe
Sinazongwe is a lakeside town in southern Zambia situated on the shores of Lake Kariba, known primarily for fishing and agriculture.
-
D.
Chiredzi
Chiredzi is a town in southeastern Zimbabwe known as a center for sugarcane farming and a gateway to nearby wildlife and conservation areas.
-
E.
Zvimba
Zvimba is a town in northern Zimbabwe located within Mashonaland West Province, known primarily as a rural administrative and farming center.
- F. None of above. chosen
Provenance (5 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d81c71b1208190be1d5623d18e0222 |
completed | April 9, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5d3e197c881909db2e4e59c61c3c3 |
completed | April 20, 2026, 7:21 a.m. |
| NEDg | Description generation | batch_69e5d5cc251081908b85f264940a6545 |
completed | April 20, 2026, 7:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5d924963c8190bfc55ffeb529a499 |
completed | April 20, 2026, 7:43 a.m. |
Created at: April 8, 2026, 9:35 p.m.