Triple
T15694291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuglhorn |
E380415
|
entity |
| Predicate | hasSceneryCharacteristic |
P22129
|
FINISHED |
| Object | steep slopes |
—
|
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: steep slopes | Statement: [Kuglhorn, hasSceneryCharacteristic, steep slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSceneryCharacteristic Context triple: [Kuglhorn, hasSceneryCharacteristic, steep slopes]
-
A.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
B.
hasScenicResource
Indicates that an entity possesses or is associated with a natural or visual feature valued for its aesthetic or scenic qualities.
-
C.
hasGeographyCharacteristic
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
D.
hasLandscapeFeatures
chosen
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
E.
isScenicArea
Indicates that a location is recognized as a scenic area, typically valued for its natural beauty or visually appealing surroundings.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0051d639481909a10614e8f83e659 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:44 a.m.