Triple
T35059385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Route 179 Scenic Byway |
E1011550
|
entity |
| Predicate | primaryLandscapeColor |
P24916
|
FINISHED |
| Object | red rock |
—
|
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: red rock | Statement: [State Route 179 Scenic Byway, primaryLandscapeColor, red rock]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLandscapeColor Context triple: [State Route 179 Scenic Byway, primaryLandscapeColor, red rock]
-
A.
primaryColorPalette
Indicates the set of main or dominant colors associated with an entity, typically used as its core color scheme.
-
B.
primaryColour
chosen
Indicates that one entity is the main or dominant color characteristic of another entity.
-
C.
primaryLandscape
Indicates that one landscape serves as the main or most characteristic environmental setting associated with an entity or context.
-
D.
primaryColorProduction
Indicates that an entity is responsible for producing or generating a primary color (such as red, blue, or yellow) in some context.
-
E.
primaryWavelength
Indicates the main or dominant wavelength associated with an entity, such as the principal wavelength at which it emits, reflects, or operates.
- 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_69f76dd09c308190a523454853ce842b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.