Triple
T7657073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hluhluwe–iMfolozi Park |
E173410
|
entity |
| Predicate | distanceFromDurban |
P34438
|
FINISHED |
| Object | about 250 kilometres |
—
|
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 250 kilometres | Statement: [Hluhluwe–iMfolozi Park, distanceFromDurban, about 250 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDurban Context triple: [Hluhluwe–iMfolozi Park, distanceFromDurban, about 250 kilometres]
-
A.
distanceToDurban_km
chosen
Indicates the physical distance, measured in kilometers, between a given location and the city of Durban.
-
B.
distanceFromCapeTown
Indicates the measured distance between a given location and Cape Town.
-
C.
distanceToJohannesburg_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Johannesburg.
-
D.
distanceToNelspruit
Indicates the spatial distance between a given entity’s location and the location of Nelspruit.
-
E.
distanceToSouthAfrica
Indicates the measured or calculated spatial distance between a given entity and the country of South Africa.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7061cbc3c8190a917dd7e71214182 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015dd8fc8190bc5f52a12bd46209 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 3:59 p.m.