Triple
T26220304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cullinan mine |
E655746
|
entity |
| Predicate | distanceFromPretoria_km |
P98764
|
FINISHED |
| Object | about 40 |
—
|
LITERAL 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: about 40 | Statement: [Cullinan mine, distanceFromPretoria_km, about 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPretoria_km Context triple: [Cullinan mine, distanceFromPretoria_km, about 40]
-
A.
distanceFromPretoria
chosen
Indicates the spatial distance between a given entity or location and the city of Pretoria.
-
B.
approximateDistanceToPretoria
Indicates that one entity has an estimated or rough distance measurement relative to the location of Pretoria.
-
C.
distanceToJohannesburg_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Johannesburg.
-
D.
distanceFromMahikeng
Indicates the measured distance between a given entity and the location of Mahikeng.
-
E.
distanceToDurban_km
Indicates the physical distance, measured in kilometers, between a given location and the city of Durban.
- F. None of above.
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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: April 26, 2026, 8:55 p.m.