Triple
T5601371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bamaga |
E147126
|
entity |
| Predicate | distanceToTipOfCapeYork |
P64987
|
FINISHED |
| Object | approximately 40 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: approximately 40 kilometres | Statement: [Bamaga, distanceToTipOfCapeYork, approximately 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTipOfCapeYork Context triple: [Bamaga, distanceToTipOfCapeYork, approximately 40 kilometres]
-
A.
distanceToDarwin
Indicates the spatial distance between a given entity’s location and the location of Darwin.
-
B.
distanceFromDarwin
Indicates the spatial distance between an entity and the location Darwin.
-
C.
distanceToGreatBarrierReef
Indicates the spatial distance between a given entity and the Great Barrier Reef.
-
D.
distanceToGympie
Indicates the spatial distance between a given location and the town or area of Gympie.
-
E.
distanceToForster_km
Indicates the physical distance, measured in kilometers, between an entity and a reference location named Forster.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020da519c81908626b243e40db263 |
completed | March 22, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69c01b1890ec8190b9e6fa488792e4d4 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:39 p.m.