Triple
T13480609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee Bay |
E318360
|
entity |
| Predicate | distanceToMthatha |
P110555
|
FINISHED |
| Object | approximately 80 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 80 km | Statement: [Coffee Bay, distanceToMthatha, approximately 80 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMthatha Context triple: [Coffee Bay, distanceToMthatha, approximately 80 km]
-
A.
distanceFromPretoria
Indicates the spatial distance between a given entity or location and the city of Pretoria.
-
B.
distanceToNelspruit
Indicates the spatial distance between a given entity’s location and the location of Nelspruit.
-
C.
distanceToJohannesburg_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Johannesburg.
-
D.
distanceToDurban_km
Indicates the physical distance, measured in kilometers, between a given location and the city of Durban.
-
E.
distanceFromBulawayo
Indicates the measured spatial distance between a given location or entity and the city of Bulawayo.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf36c6b08190ba99400600e0b662 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:42 p.m.