Triple
T14923534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CES |
E371573
|
entity |
| Predicate | spectralResolutionType |
P7238
|
FINISHED |
| Object | high-dispersion |
—
|
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: high-dispersion | Statement: [CES, spectralResolutionType, high-dispersion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spectralResolutionType Context triple: [CES, spectralResolutionType, high-dispersion]
-
A.
spectralResolution
chosen
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
B.
hasSpatialResolution
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
-
C.
spectrometerType
Indicates the specific kind or category of spectrometer associated with or used in relation to an entity.
-
D.
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).
-
E.
hasSpectralChannel
Indicates that something possesses or is associated with a specific spectral channel or band within an electromagnetic spectrum.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6323f8c8190af02d06352d459c3 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:34 a.m.