Triple
T27846050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darreh Setarehā |
E703822
|
entity |
| Predicate | landscapeAppearance |
P163415
|
FINISHED |
| Object | otherworldly |
—
|
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: otherworldly | Statement: [Darreh Setarehā, landscapeAppearance, otherworldly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landscapeAppearance Context triple: [Darreh Setarehā, landscapeAppearance, otherworldly]
-
A.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
-
B.
landscapeView
Indicates that one entity provides or features a scenic or panoramic view of a landscape from the perspective of another entity.
-
C.
landscapeElement
Indicates that one entity functions as a landscape-related feature or component in relation to another entity.
-
D.
landscapeValue
Indicates the assessed aesthetic, cultural, or ecological worth attributed to a particular landscape or scenery.
-
E.
landscapeEffect
Indicates how a particular landscape or terrain influences or modifies the outcome, behavior, or characteristics of another entity or process.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f638da9bcc8190b6064afb5bcf17ec |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
| PDg | Predicate description generation | batch_69f6359d46b88190922dd7de508e3b0e |
completed | May 2, 2026, 5:34 p.m. |
Created at: April 27, 2026, 6:07 p.m.