Triple
T19133027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | (19308) 1996 TO66 |
E468360
|
entity |
| Predicate | spectralSlope |
P48586
|
FINISHED |
| Object | low (blue-neutral) |
—
|
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: low (blue-neutral) | Statement: [(19308) 1996 TO66, spectralSlope, low (blue-neutral)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spectralSlope Context triple: [(19308) 1996 TO66, spectralSlope, low (blue-neutral)]
-
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.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
C.
spectralMeasure
Indicates a relationship where a measure assigns values to sets in a spectrum, typically capturing how a quantity (like probability or mass) is distributed across spectral components.
-
D.
positionOnSpectrum
Indicates the relative location or value of something along a defined continuum or range of possible states.
-
E.
spectralClass
Indicates the classification of an astronomical object based on the characteristics of its spectrum, such as temperature and spectral features.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3ea82f08190811ef35fbae744d1 |
completed | April 20, 2026, 8:29 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.