Triple
T10743023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelly Beach (Port Macquarie) |
E253374
|
entity |
| Predicate | hasNaturalSetting |
P1094
|
FINISHED |
| Object | seaside |
—
|
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: seaside | Statement: [Shelly Beach (Port Macquarie), hasNaturalSetting, seaside]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNaturalSetting Context triple: [Shelly Beach (Port Macquarie), hasNaturalSetting, seaside]
-
A.
hasNature
Indicates that something possesses, exhibits, or is characterized by a particular inherent quality, essence, or fundamental type.
-
B.
hasNaturalProtection
Indicates that an entity is safeguarded by inherent or environmental protective features (such as terrain, vegetation, or natural barriers) rather than by artificial defenses.
-
C.
hasNaturalAreaType
Indicates that an entity is associated with or classified by a specific type of natural area (e.g., forest, wetland, grassland).
-
D.
hasNaturalFeature
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
E.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d711b5dd8c81908f1d9b126e4c3ae7 |
completed | April 9, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:15 p.m.