Triple
T11258827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandton |
E266508
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Illovo |
E712428
|
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: Illovo | Statement: [Sandton, hasPart, Illovo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Illovo Context triple: [Sandton, hasPart, Illovo]
-
A.
Illovo
chosen
Illovo is an affluent commercial and residential suburb in Johannesburg, South Africa, known for its corporate offices, upscale apartments, and proximity to major business and educational institutions.
-
B.
Tembisa
Tembisa is a large township in Gauteng, South Africa, situated on the East Rand and known as a densely populated residential area within the City of Ekurhuleni.
-
C.
Emgesa
Emgesa is an energy company that operates hydroelectric power facilities in Colombia.
-
D.
Thohoyandou
Thohoyandou is a town in South Africa’s Limpopo province that serves as an administrative, commercial, and educational hub for the surrounding region.
-
E.
Nongoma
Nongoma is a town in KwaZulu-Natal, South Africa, historically significant as a center of Zulu royalty and traditional leadership.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e936cb048190b4d6fb2851ef8932 |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ccada158819080e49833e09f84a0 |
completed | April 19, 2026, 12:38 p.m. |
Created at: April 8, 2026, 9:31 p.m.