Triple
T2697972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broken Hill region of New South Wales |
E58557
|
entity |
| Predicate | distanceFromSydney_km_approx |
P15398
|
FINISHED |
| Object | 1100 |
—
|
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: 1100 | Statement: [Broken Hill region of New South Wales, distanceFromSydney_km_approx, 1100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSydney_km_approx Context triple: [Broken Hill region of New South Wales, distanceFromSydney_km_approx, 1100]
-
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.
distanceToBrisbane_km
Indicates the physical distance, measured in kilometers, between a given location and Brisbane.
-
D.
distanceToAdelaide_km
Indicates the physical distance, measured in kilometers, between a given location and Adelaide.
-
E.
distanceFromBrisbane
Indicates the measured distance between a given location or entity and the city of Brisbane.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda322af48190833b8a3c006db236 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ea5d88190ab5c8f8b8064b931 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.