Triple
T22027013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CIE standard illuminant D50 |
E543993
|
entity |
| Predicate | spectralPowerDistributionType |
P146316
|
FINISHED |
| Object | daylight |
—
|
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: daylight | Statement: [CIE standard illuminant D50, spectralPowerDistributionType, daylight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spectralPowerDistributionType Context triple: [CIE standard illuminant D50, spectralPowerDistributionType, daylight]
-
A.
spectralProperty
Indicates a relationship where an entity possesses or is characterized by a specific spectral feature, measurement, or behavior (e.g., in its frequency, wavelength, or energy spectrum).
-
B.
emitsSpectrum
Indicates that one entity produces or gives off electromagnetic radiation characterized by a particular spectrum.
-
C.
spectralRegion
Indicates the portion of the electromagnetic spectrum (e.g., wavelength or frequency range) in which a measurement, observation, or property is defined or applies.
-
D.
opticalProperty
Indicates a relationship where an entity has or is characterized by a specific optical property, such as how it interacts with or responds to light.
-
E.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127ccc2ec8190a94d69530d00c06c |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:24 p.m.