Triple
T19425821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American picturesque movement |
E485976
|
entity |
| Predicate | typicalLandscapeFeature |
P5378
|
FINISHED |
| Object | winding paths |
—
|
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: winding paths | Statement: [American picturesque movement, typicalLandscapeFeature, winding paths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLandscapeFeature Context triple: [American picturesque movement, typicalLandscapeFeature, winding paths]
-
A.
terrainFeature
chosen
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
B.
mountainFeature
Indicates that one entity is a notable physical or geographical feature associated with, located on, or forming part of a mountain.
-
C.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
D.
physicalFeature
Indicates that one entity possesses or exhibits a particular physical characteristic or attribute.
-
E.
isNaturalFeature
Indicates that the subject is a naturally occurring physical feature of the environment, not created or significantly altered by human activity.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63218772c8190a48b6cb01bd12b73 |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.