Triple
T11976282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emfuleni Local Municipality |
E285048
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Vanderbijlpark |
E58237
|
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: Vanderbijlpark | Statement: [Emfuleni Local Municipality, contains, Vanderbijlpark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanderbijlpark Context triple: [Emfuleni Local Municipality, contains, Vanderbijlpark]
-
A.
Vanderbijlpark
chosen
Vanderbijlpark is an industrial city in South Africa known for its large steel production facilities and location on the Vaal River.
-
B.
Roodepoort
Roodepoort is a suburban city on the western side of Johannesburg in South Africa, known for its residential areas, shopping centers, and proximity to the Witwatersrand hills.
-
C.
Durbanville
Durbanville is a suburban town in the northern outskirts of Cape Town, South Africa, known for its wine estates and residential character.
-
D.
Krugersdorp
Krugersdorp is a historic mining town in South Africa known for its gold deposits and location on the West Rand of the Gauteng province.
-
E.
Calitzdorp
Calitzdorp is a small town in South Africa’s Western Cape renowned for its port-style wines and scenic setting along Route 62.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903926690819090e7ce982f103457 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63edbcd288190b491a16f2bf8fc62 |
completed | May 2, 2026, 6:13 p.m. |
Created at: April 8, 2026, 9:46 p.m.