Triple
T19296082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Coquelicots (Claude Monet) |
E482564
|
entity |
| Predicate | skyType |
P349
|
FINISHED |
| Object | bright airy sky |
—
|
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: bright airy sky | Statement: [Les Coquelicots (Claude Monet), skyType, bright airy sky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skyType Context triple: [Les Coquelicots (Claude Monet), skyType, bright airy sky]
-
A.
skyQuality
chosen
Indicates the measured level or condition of the sky, typically in terms of clarity, brightness, or suitability for observation.
-
B.
skyTreatment
Indicates the method or process applied to alter, enhance, or manage the appearance or condition of the sky.
-
C.
skyRole
Indicates a role or function that an entity has specifically in relation to the sky or sky-related phenomena.
-
D.
darkSkyRecognition
Indicates formal recognition that a location meets specific criteria for dark sky quality, such as minimal light pollution and suitability for stargazing or astronomical observation.
-
E.
skyHemisphere
Indicates the celestial hemisphere (e.g., northern or southern part of the sky) in which an astronomical object or event is located or observed.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc8533c08190822a917ffa32812d |
completed | April 20, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:31 p.m.