Triple
T21730959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Era Beach |
E536402
|
entity |
| Predicate | nearestAccessPoint |
P61475
|
FINISHED |
| Object | Garie Beach car park |
—
|
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: Garie Beach car park | Statement: [North Era Beach, nearestAccessPoint, Garie Beach car park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestAccessPoint Context triple: [North Era Beach, nearestAccessPoint, Garie Beach car park]
-
A.
nearestPass
Indicates that one entity is the closest in distance or proximity to another entity compared to all other possible entities or paths.
-
B.
bestAccessPoint
Indicates that one access point is considered the most suitable or optimal choice for connecting to a given entity or location among available alternatives.
-
C.
nearestArea
Indicates that one area is the closest in distance to a given reference point or region compared to all other candidate areas.
-
D.
nearestPointTo
Indicates the point that is closest in distance to a given reference point or object among a set of candidates.
-
E.
nearestEntrance
chosen
Indicates that one entrance is the closest access point to a given location or entity compared to all other possible entrances.
- 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_69e0c46d3284819099a4f9d5a704eb95 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69effd064fcc819084852b4248f65a81 |
completed | April 28, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:48 p.m.