Triple
T3534045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairy Meadow |
E74726
|
entity |
| Predicate | distanceToWollongongCBD |
P48154
|
FINISHED |
| Object | approximately 4 km north |
—
|
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 4 km north | Statement: [Fairy Meadow, distanceToWollongongCBD, approximately 4 km north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToWollongongCBD Context triple: [Fairy Meadow, distanceToWollongongCBD, approximately 4 km north]
-
A.
distanceFromGosford_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Gosford.
-
B.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
-
C.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
D.
distanceToMelbourne
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
E.
distanceFromBrisbane
Indicates the measured distance between a given location or entity and the city of Brisbane.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc9cff5c81909011f34c9bf28e11 |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae13ab808190a5d6ecdc7543445e |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed7f2ec819085467d281712e0e8 |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:19 p.m.