Triple
T19937990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eerste River |
E479224
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Stellenbosch town |
—
|
NE NERFINISHED |
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: Stellenbosch town | Statement: [Eerste River, near, Stellenbosch town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stellenbosch town Context triple: [Eerste River, near, Stellenbosch town]
-
A.
Muizenberg
Muizenberg is a seaside suburb of Cape Town, South Africa, known for its popular surfing beach and colorful Victorian beach huts.
-
B.
Paarl
Paarl is a historic town in South Africa renowned for its wine estates, scenic granite rock formations, and role in the development of the Afrikaans language.
-
C.
Rondebosch
Rondebosch is a leafy, affluent suburb in Cape Town, South Africa, known for its academic character and proximity to major educational institutions.
-
D.
Stellenbosch
chosen
Stellenbosch is a historic South African town renowned for its wine estates, Cape Dutch architecture, and role as an academic center through Stellenbosch University.
-
E.
Swellendam
Swellendam is a historic town in South Africa’s Western Cape, known for its Cape Dutch architecture and location near the Langeberg Mountains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a190ac08190b9dc7955c9764a71 |
completed | April 20, 2026, 4:53 p.m. |
Created at: April 10, 2026, 1:53 p.m.