Triple
T6986440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albury railway station |
E161973
|
entity |
| Predicate | distanceFromMelbourneSouthernCross |
P21893
|
FINISHED |
| Object | 326 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: 326 km | Statement: [Albury railway station, distanceFromMelbourneSouthernCross, 326 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMelbourneSouthernCross Context triple: [Albury railway station, distanceFromMelbourneSouthernCross, 326 km]
-
A.
distanceToMelbourne
chosen
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
B.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
-
C.
distanceFromGeelong
Indicates the spatial distance between a given entity or location and Geelong.
-
D.
approxDrivingTimeFromMelbourne
Indicates the estimated duration it takes to drive from Melbourne to a specified location.
-
E.
distanceFromGosford_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Gosford.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbbd926c8190a8b60527bd553fa3 |
completed | March 27, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c4a18881908d267137daed828b |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:32 p.m.