Triple
T2727761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yulara |
E60233
|
entity |
| Predicate | distanceFromAliceSpringsByRoad_km |
P13339
|
FINISHED |
| Object | about 440 |
—
|
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 440 | Statement: [Yulara, distanceFromAliceSpringsByRoad_km, about 440]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromAliceSpringsByRoad_km Context triple: [Yulara, distanceFromAliceSpringsByRoad_km, about 440]
-
A.
distanceFromAliceSprings
chosen
Indicates the spatial distance between a given location or entity and Alice Springs.
-
B.
distanceToAdelaide_km
Indicates the physical distance, measured in kilometers, between a given location and Adelaide.
-
C.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
D.
distanceFromAlbury
Indicates the spatial distance between a given entity or location and the place named Albury.
-
E.
distanceToBrisbane_km
Indicates the physical distance, measured in kilometers, between a given location and 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdacffa6481909df37335e8fdd595 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd82586f88190a98f60d3247fe2d3 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.