Triple
T2698040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice Springs |
E58559
|
entity |
| Predicate | distanceToAdelaide |
P27723
|
FINISHED |
| Object | about 1500 km by road |
—
|
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 1500 km by road | Statement: [Alice Springs, distanceToAdelaide, about 1500 km by road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAdelaide Context triple: [Alice Springs, distanceToAdelaide, about 1500 km by road]
-
A.
distanceToAdelaide_km
chosen
Indicates the physical distance, measured in kilometers, between a given location and Adelaide.
-
B.
distanceToMelbourne
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
C.
distanceToPerth
Indicates the measured distance between a given entity’s location and the city of Perth.
-
D.
distanceFromAlbury
Indicates the spatial distance between a given entity or location and the place named Albury.
-
E.
distanceToGoldCoast
Indicates the measured distance between a given entity and the location known as the Gold Coast.
- 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.