Triple
T25245183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ballypatrick |
E632579
|
entity |
| Predicate | hasScenicCountrysideSetting |
P6652
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ballypatrick, hasScenicCountrysideSetting, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScenicCountrysideSetting Context triple: [Ballypatrick, hasScenicCountrysideSetting, true]
-
A.
hasRuralLandscapeType
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
B.
isScenicTown
Indicates that a town is visually attractive or picturesque, often due to its natural surroundings, architecture, or overall aesthetic appeal.
-
C.
hasScenicValue
chosen
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
D.
isScenicArea
Indicates that a location is recognized as a scenic area, typically valued for its natural beauty or visually appealing surroundings.
-
E.
hasScenicPassNearby
Indicates that a location is situated close to a notable scenic pass, such as a mountain or landscape viewpoint route.
- 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_69e75a8fdd3881909ba0b05aa5da92a7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 1:10 p.m.