Triple
T6169462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Griffith railway station |
E137653
|
entity |
| Predicate | distanceFromSydneyCentralByRail_km |
P15398
|
FINISHED |
| Object | about 640 |
—
|
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 640 | Statement: [Griffith railway station, distanceFromSydneyCentralByRail_km, about 640]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSydneyCentralByRail_km Context triple: [Griffith railway station, distanceFromSydneyCentralByRail_km, about 640]
-
A.
distanceFromSydney
chosen
Indicates the spatial distance between a given location and the city of Sydney.
-
B.
distanceToBrisbane_km
Indicates the physical distance, measured in kilometers, between a given location and Brisbane.
-
C.
distanceToMelbourne
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
D.
distanceFromBrisbane
Indicates the measured distance between a given location or entity and the city of Brisbane.
-
E.
distanceToAdelaide_km
Indicates the physical distance, measured in kilometers, between a given location and Adelaide.
- 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_69c008a68c508190a8d78245c865960e |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d8f97708190bebbc49c4a56c8a5 |
completed | March 22, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69c055f7f12881908e21c04e9b752ba4 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:18 p.m.