Triple
T10921373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sapodilla Bay Beach |
E257953
|
entity |
| Predicate | hasShorelineShape |
P6651
|
FINISHED |
| Object | curved bay |
—
|
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: curved bay | Statement: [Sapodilla Bay Beach, hasShorelineShape, curved bay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShorelineShape Context triple: [Sapodilla Bay Beach, hasShorelineShape, curved bay]
-
A.
hasShorelineMarker
Indicates that a location or area is marked or delineated by a designated shoreline indicator or boundary marker.
-
B.
hasShoreFeature
chosen
Indicates that a shore or coastline possesses a specific physical or environmental feature.
-
C.
hasShorelineCountry
Indicates that a country possesses a coastline or land boundary directly adjacent to a particular body of water or coastal region.
-
D.
hasShorelineUse
Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
-
E.
hasLongShoreline
Indicates that an entity possesses an extensive or unusually long shoreline relative to typical cases.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77082a1488190850a4409339c3e1e |
completed | April 9, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69d72e799f808190b6ab64fc7586a303 |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:22 p.m.