Triple
T4879053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiʻiaka |
E109278
|
entity |
| Predicate | spectralFeatures |
P48586
|
FINISHED |
| Object | strong water-ice absorption bands |
—
|
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: strong water-ice absorption bands | Statement: [Hiʻiaka, spectralFeatures, strong water-ice absorption bands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spectralFeatures Context triple: [Hiʻiaka, spectralFeatures, strong water-ice absorption bands]
-
A.
spectralProperty
chosen
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.
hasSpectralChannel
Indicates that something possesses or is associated with a specific spectral channel or band within an electromagnetic spectrum.
-
C.
sharesFeatureExtractor
Indicates that two or more models or components use the same feature extraction mechanism or module.
-
D.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
E.
compositionalFeature
Indicates that one entity is a structural or constituent feature that forms part of the composition or makeup of another entity.
- 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_69bd440e9d64819083e82cf33b4d9570 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6dbf37ac819085bb758bc6406271 |
completed | March 20, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2be5e881909f6ec9c3bcde49f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:27 p.m.