Triple
T26052128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Struisbaai |
E648006
|
entity |
| Predicate | distanceFromCapeAgulhas |
P193590
|
FINISHED |
| Object | approximately 4–5 km |
—
|
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: approximately 4–5 km | Statement: [Struisbaai, distanceFromCapeAgulhas, approximately 4–5 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromCapeAgulhas Context triple: [Struisbaai, distanceFromCapeAgulhas, approximately 4–5 km]
-
A.
distanceFromCapeTown
Indicates the measured distance between a given location and Cape Town.
-
B.
distanceFromNorthCape
Indicates the measured distance of an entity from the geographic location known as the North Cape.
-
C.
distanceToRichardsBay_km
Indicates the physical distance, measured in kilometers, between a given location and Richards Bay.
-
D.
distanceFromPortElizabeth_km
Indicates the distance, measured in kilometers, between a given location and Port Elizabeth.
-
E.
distanceToSaintHelena
Indicates the measured distance between a given entity and the location of Saint Helena.
- F. None of above. chosen
Provenance (4 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_69e77e8d419481908004e6318d28aaab |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
| PDg | Predicate description generation | batch_69fd4d16dd20819096957c40f43cd971 |
completed | May 8, 2026, 2:40 a.m. |
Created at: April 22, 2026, 9:11 a.m.