Triple
T759387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johannesburg |
E16031
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Joburg |
E16031
|
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: Joburg | Statement: [Johannesburg, nickname, Joburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joburg Context triple: [Johannesburg, nickname, Joburg]
-
A.
Johannesburg, South Africa
chosen
Johannesburg, South Africa is the country’s largest city and economic hub, known for its role in the gold mining industry and as a major urban center in Gauteng province.
-
B.
Cape Town
Cape Town is a major coastal city in South Africa known for its iconic Table Mountain, diverse culture, and role as the country’s legislative capital.
-
C.
Durban
Durban is a major coastal city in South Africa known for its busy port, subtropical climate, and significant Indian community.
-
D.
Pretoria, South Africa
Pretoria, South Africa is one of the country’s three capital cities, serving as the administrative capital and a major center for government, education, and culture.
-
E.
Randburg
Randburg is a residential and commercial suburb in the north of Johannesburg, South Africa, known for its shopping centers, business districts, and leafy neighborhoods.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a67f9778819098d3c144dd26b976 |
completed | March 1, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf4d769c81909eba6cefb241d417 |
completed | March 4, 2026, 6:21 a.m. |
Created at: March 1, 2026, 7:37 p.m.