Triple
T19321846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R Scuti |
E483243
|
entity |
| Predicate | spectralClassRange |
P69243
|
FINISHED |
| Object | G–K supergiant |
—
|
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: G–K supergiant | Statement: [R Scuti, spectralClassRange, G–K supergiant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spectralClassRange Context triple: [R Scuti, spectralClassRange, G–K supergiant]
-
A.
spectralClass
Indicates the classification of an astronomical object based on the characteristics of its spectrum, such as temperature and spectral features.
-
B.
hasSpectralTypeRange
chosen
Indicates that an entity is associated with a specified range of spectral types rather than a single, discrete spectral classification.
-
C.
dominantSpectralType
Indicates the primary or most prevalent spectral type characterizing the electromagnetic emission of an object or region.
-
D.
hasStellarSpectrum
Indicates that an astronomical object exhibits a particular stellar spectrum characterizing its emitted light across wavelengths.
-
E.
trumplerClassification
Indicates the classification of a star cluster according to the Trumpler system, describing its concentration, range of brightness, and richness.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d8948948190b76a384041333509 |
completed | April 20, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.