Triple
T33900003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | α Aquarii |
E869019
|
entity |
| Predicate | belongsToLuminosityClass |
P22859
|
FINISHED |
| Object | Ib |
—
|
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: Ib | Statement: [α Aquarii, belongsToLuminosityClass, Ib]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToLuminosityClass Context triple: [α Aquarii, belongsToLuminosityClass, Ib]
-
A.
luminosityClass
chosen
Indicates the stellar luminosity classification that specifies a star’s intrinsic brightness and evolutionary stage.
-
B.
spectralClass
Indicates the classification of an astronomical object based on the characteristics of its spectrum, such as temperature and spectral features.
-
C.
trumplerClassification
Indicates the classification of a star cluster according to the Trumpler system, describing its concentration, range of brightness, and richness.
-
D.
dominantSpectralType
Indicates the primary or most prevalent spectral type characterizing the electromagnetic emission of an object or region.
-
E.
hasStellarMassClass
Indicates the classification relationship that assigns an object to a specific category based on its stellar mass.
- 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_69f34997703c8190866b1d404bce531f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff38b960808190a8263348f1e5c0e4 |
completed | May 9, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69ff37d97d9c8190849b2bac14f9af1d |
completed | May 9, 2026, 1:34 p.m. |
Created at: May 1, 2026, 1:48 a.m.