Triple
T15252101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Wollongong railway station |
E364541
|
entity |
| Predicate | distanceFromSydneyTerminal |
P15398
|
FINISHED |
| Object | approximately 82 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 82 kilometres | Statement: [North Wollongong railway station, distanceFromSydneyTerminal, approximately 82 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSydneyTerminal Context triple: [North Wollongong railway station, distanceFromSydneyTerminal, approximately 82 kilometres]
-
A.
distanceFromSydney
chosen
Indicates the spatial distance between a given location and the city of Sydney.
-
B.
distanceToMelbourne
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
C.
distanceToDarwin
Indicates the spatial distance between a given entity’s location and the location of Darwin.
-
D.
distanceFromBrisbane
Indicates the measured distance between a given location or entity and the city of Brisbane.
-
E.
distanceFromFlindersStreet
Indicates the spatial distance between a given location and Flinders Street.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f728648190b2c86e4528542b65 |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca8d1bd48190a4b94f29b425e335 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:13 a.m.