Triple
T583110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Mountains |
E15098
|
entity |
| Predicate | approximateDistanceFromSydney |
P15398
|
FINISHED |
| Object | 50–100 kilometres west |
—
|
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: 50–100 kilometres west | Statement: [Blue Mountains, approximateDistanceFromSydney, 50–100 kilometres west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceFromSydney Context triple: [Blue Mountains, approximateDistanceFromSydney, 50–100 kilometres west]
-
A.
distanceFromSydney
chosen
Indicates the spatial distance between a given location and the city of Sydney.
-
B.
distanceToPerth
Indicates the measured distance between a given entity’s location and the city of Perth.
-
C.
distanceFromSanFrancisco
Indicates the measured distance between a given entity’s location and the city of San Francisco.
-
D.
distanceFromSouthPole
Indicates the measured distance of an entity from the geographic South Pole.
-
E.
distanceToNewYorkCity
Indicates the spatial distance between a given entity’s location and New York City.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b85becc8190b4d98c00e5fa7c04 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c9315c8190a773e8e00737d8a0 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.