Triple
T556720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gloucester (former local government area) |
E11956
|
entity |
| Predicate | scenicQuality |
P6652
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Gloucester (former local government area), scenicQuality, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenicQuality Context triple: [Gloucester (former local government area), scenicQuality, high]
-
A.
hasScenicValue
chosen
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
B.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
C.
hasMountainScenery
Indicates that a place or area features views or landscapes dominated by mountains.
-
D.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
-
E.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991ef9b0819092ec0407270373f4 |
completed | March 1, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.