Triple
T13992518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaal Dam |
E336615
|
entity |
| Predicate | suppliesWaterTo |
P4102
|
FINISHED |
| Object | Sasolburg |
E135668
|
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: Sasolburg | Statement: [Vaal Dam, suppliesWaterTo, Sasolburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sasolburg Context triple: [Vaal Dam, suppliesWaterTo, Sasolburg]
-
A.
Sasolburg
chosen
Sasolburg is an industrial town in South Africa’s Free State province, known primarily for its large petrochemical complex and proximity to the Vaal River.
-
B.
Rustenburg
Rustenburg is a city in South Africa’s North West Province known for its mining industry and as one of the venues for the 2010 FIFA World Cup.
-
C.
Bothasig
Bothasig is a residential suburb in the northern part of Cape Town, South Africa.
-
D.
Cornberg
Cornberg is a small municipality in the German state of Hesse, known for its rural setting and historical monastery complex.
-
E.
Colesberg
Colesberg is a small historic town in South Africa’s Northern Cape, known as a key stopover on the N1 highway and a gateway to the semi-arid Karoo region.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb3b5d881909f15a1e08bb202f3 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac98ca448190b585ef69a4e4bfca |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:19 p.m.