Triple
T27502214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandy Bay |
E694185
|
entity |
| Predicate | hasSceneryStyle |
P174348
|
FINISHED |
| Object | traditional New England seascape |
—
|
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: traditional New England seascape | Statement: [Sandy Bay, hasSceneryStyle, traditional New England seascape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSceneryStyle Context triple: [Sandy Bay, hasSceneryStyle, traditional New England seascape]
-
A.
hasScenicResource
Indicates that an entity possesses or is associated with a natural or visual feature valued for its aesthetic or scenic qualities.
-
B.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
C.
hasScenicRouteType
Indicates that a route is associated with a specific type or category of scenic quality or scenic designation.
-
D.
hasExteriorStyle
Indicates that an entity possesses or is characterized by a particular exterior design or stylistic appearance.
-
E.
hasScenicSections
Indicates that a route, path, or area contains segments that are visually attractive or offer notable scenic views.
- 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_69ef538370888190b1ddf53bb4831188 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6c20f209081909fb9ac8f95069f04 |
completed | May 3, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c125695c81909704c67bef4ce5b2 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 27, 2026, 1:11 p.m.