Triple
T5061334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurieton |
E114028
|
entity |
| Predicate | distanceToPortMacquarie_km |
P34514
|
FINISHED |
| Object | approximately 40 |
—
|
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 40 | Statement: [Laurieton, distanceToPortMacquarie_km, approximately 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPortMacquarie_km Context triple: [Laurieton, distanceToPortMacquarie_km, approximately 40]
-
A.
distanceToPortMacquarieKilometres
chosen
Indicates the distance, measured in kilometres, between a given entity’s location and Port Macquarie.
-
B.
distanceToForster_km
Indicates the physical distance, measured in kilometers, between an entity and a reference location named Forster.
-
C.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
-
D.
distanceToBrisbane_km
Indicates the physical distance, measured in kilometers, between a given location and Brisbane.
-
E.
directionFrom_PortMacquarie
Indicates the compass direction in which one location lies relative to Port Macquarie.
- 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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74740ae08190930f1fd57187334e |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.