Triple
T12966598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mbongeni Ngema |
E321277
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Verulam, KwaZulu-Natal
Verulam, KwaZulu-Natal is a town in South Africa’s KwaZulu-Natal province, located north of Durban and known for its diverse community and sugarcane farming.
|
E1013182
|
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: Verulam, KwaZulu-Natal | Statement: [Mbongeni Ngema, placeOfBirth, Verulam, KwaZulu-Natal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verulam, KwaZulu-Natal Context triple: [Mbongeni Ngema, placeOfBirth, Verulam, KwaZulu-Natal]
-
A.
Ladysmith, KwaZulu-Natal
Ladysmith, KwaZulu-Natal is a historic town in South Africa known for its role in the Anglo-Boer War and as a regional commercial and transport hub.
-
B.
Tzaneen
Tzaneen is a large agricultural town in South Africa’s Limpopo province, known for its subtropical climate and extensive fruit farming.
-
C.
Bothasig
Bothasig is a residential suburb in the northern part of Cape Town, South Africa.
-
D.
Emalahleni
Emalahleni is a major coal-mining and industrial city in South Africa’s Mpumalanga province, historically known as Witbank.
-
E.
Giyani
Giyani is a town in northeastern Limpopo, South Africa, known as an administrative and commercial center for the surrounding rural region.
- 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: Verulam, KwaZulu-Natal Triple: [Mbongeni Ngema, placeOfBirth, Verulam, KwaZulu-Natal]
Generated description
Verulam, KwaZulu-Natal is a town in South Africa’s KwaZulu-Natal province, located north of Durban and known for its diverse community and sugarcane farming.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Verulam, KwaZulu-Natal Target entity description: Verulam, KwaZulu-Natal is a town in South Africa’s KwaZulu-Natal province, located north of Durban and known for its diverse community and sugarcane farming.
-
A.
Ladysmith, KwaZulu-Natal
Ladysmith, KwaZulu-Natal is a historic town in South Africa known for its role in the Anglo-Boer War and as a regional commercial and transport hub.
-
B.
Tzaneen
Tzaneen is a large agricultural town in South Africa’s Limpopo province, known for its subtropical climate and extensive fruit farming.
-
C.
Bothasig
Bothasig is a residential suburb in the northern part of Cape Town, South Africa.
-
D.
Emalahleni
Emalahleni is a major coal-mining and industrial city in South Africa’s Mpumalanga province, historically known as Witbank.
-
E.
Giyani
Giyani is a town in northeastern Limpopo, South Africa, known as an administrative and commercial center for the surrounding rural region.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e3f702481908f0f90f4f12d3f4d |
completed | April 10, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8e4e1a48190b8f7253717746295 |
completed | May 3, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69f6b9db8164819086a3a27692d681d5 |
completed | May 3, 2026, 2:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6bb337b708190a874cec01d588236 |
completed | May 3, 2026, 3:04 a.m. |
Created at: April 9, 2026, 8:30 p.m.