Triple
T12196376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ghan |
E290594
|
entity |
| Predicate | typicalJourneyTimeAdelaideDarwin |
P104262
|
FINISHED |
| Object | about 54 hours |
—
|
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 54 hours | Statement: [The Ghan, typicalJourneyTimeAdelaideDarwin, about 54 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalJourneyTimeAdelaideDarwin Context triple: [The Ghan, typicalJourneyTimeAdelaideDarwin, about 54 hours]
-
A.
drivingTimeFromSydney
Indicates the amount of time it takes to drive from Sydney to a specified location.
-
B.
distanceToDarwin
Indicates the spatial distance between a given entity’s location and the location of Darwin.
-
C.
distanceFromDarwin
Indicates the spatial distance between an entity and the location Darwin.
-
D.
distanceToAdelaide_km
Indicates the physical distance, measured in kilometers, between a given location and Adelaide.
-
E.
approxDrivingTimeFromMelbourne
Indicates the estimated duration it takes to drive from Melbourne to a specified location.
- F. None of above. chosen
Provenance (4 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d938ca32908190bd56f563efcbe8a0 |
completed | April 10, 2026, 5:52 p.m. |
Created at: April 8, 2026, 9:50 p.m.