Triple
T3324500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gloucester, New South Wales |
E69878
|
entity |
| Predicate | distanceFromTaree |
P47292
|
FINISHED |
| Object | approximately 90 km 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: approximately 90 km west | Statement: [Gloucester, New South Wales, distanceFromTaree, approximately 90 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTaree Context triple: [Gloucester, New South Wales, distanceFromTaree, approximately 90 km west]
-
A.
distanceFromDarwin
Indicates the spatial distance between an entity and the location Darwin.
-
B.
distanceToDarwin
Indicates the spatial distance between a given entity’s location and the location of Darwin.
-
C.
distanceFromBrisbane
Indicates the measured distance between a given location or entity and the city of Brisbane.
-
D.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
E.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
- 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_69ad85a1829881908942c14075644d0d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb13ffcb48190a8b90543aac9e6e0 |
completed | March 8, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69ada42a19348190a3862ce02451f4aa |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada52716ec81908e89688a81039394 |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:11 p.m.