Triple
T19321849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R Scuti |
E483243
|
entity |
| Predicate | brightnessVariationType |
P132953
|
FINISHED |
| Object | semiregular deep and shallow minima |
—
|
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: semiregular deep and shallow minima | Statement: [R Scuti, brightnessVariationType, semiregular deep and shallow minima]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brightnessVariationType Context triple: [R Scuti, brightnessVariationType, semiregular deep and shallow minima]
-
A.
brightnessVariation
Indicates a change or fluctuation in the level of brightness of an entity over time or across conditions.
-
B.
hasVariableBrightness
chosen
Indicates that the brightness of an entity is not constant but changes over time or under different conditions.
-
C.
surfaceBrightnessClass
Indicates the qualitative classification of how bright an extended object (such as a galaxy) appears per unit area on the sky.
-
D.
rayBrightness
Indicates the intensity or luminance level associated with a specific ray.
-
E.
isBright
Indicates that an entity emits or reflects a high level of light, making it visually intense or luminous.
- 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.