Triple
T25361948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankston |
E635991
|
entity |
| Predicate | hasForeshoreReserve |
P164168
|
FINISHED |
| Object | Frankston Foreshore |
—
|
NE NERFINISHED |
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: Frankston Foreshore | Statement: [Frankston, hasForeshoreReserve, Frankston Foreshore]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasForeshoreReserve Context triple: [Frankston, hasForeshoreReserve, Frankston Foreshore]
-
A.
hasMarineReserve
Indicates that an entity possesses, includes, or is associated with a designated marine reserve area.
-
B.
hasShorelineUse
Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
-
C.
hasShorelineUseRestrictions
Indicates that there are specific rules or limitations governing how the shoreline area associated with an entity may be used or developed.
-
D.
shorelineIncludes
Indicates that a shoreline spatially contains or encompasses a specified coastal feature or segment.
-
E.
hasLongShoreline
Indicates that an entity possesses an extensive or unusually long shoreline relative to typical cases.
- 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_69e75a9b7cf481909f2dcdfb37d95ca7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f643c204508190a43fe0ec5165b01c |
completed | May 2, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
| PDg | Predicate description generation | batch_69f6430975b481909191219ad13ef77e |
completed | May 2, 2026, 6:31 p.m. |
Created at: April 21, 2026, 1:36 p.m.