Triple
T8615416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Scenic Byway |
E204022
|
entity |
| Predicate | intrinsicQuality |
P6861
|
FINISHED |
| Object | scenic |
—
|
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: scenic | Statement: [New York State Scenic Byway, intrinsicQuality, scenic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intrinsicQuality Context triple: [New York State Scenic Byway, intrinsicQuality, scenic]
-
A.
storageQuality
Indicates the degree or standard of how well something is stored, such as its preservation, safety, or suitability for use.
-
B.
quality
chosen
Indicates that an entity possesses a particular attribute, characteristic, or degree of excellence that defines how good, suitable, or effective it is in a given context.
-
C.
hasPerceptualQuality
Indicates that something possesses a particular sensory or perceptual characteristic, such as a color, sound, texture, taste, or smell.
-
D.
imageQuality
Indicates the assessed level or degree of visual clarity, detail, and overall fidelity of an image.
-
E.
hasSurfaceQuality
Indicates that one entity possesses a particular characteristic or condition of its surface.
- 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_69ca832ceab8819096e4a9f546695079 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc47020748819090f658c115c1a7b9 |
completed | March 31, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cc455437488190b7506f820daf6e32 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:25 p.m.