Triple
T21392789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carina dSph |
E527699
|
entity |
| Predicate | surfaceBrightness_V_mag_arcsec2 |
P61265
|
FINISHED |
| Object | ~25 |
—
|
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: ~25 | Statement: [Carina dSph, surfaceBrightness_V_mag_arcsec2, ~25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surfaceBrightness_V_mag_arcsec2 Context triple: [Carina dSph, surfaceBrightness_V_mag_arcsec2, ~25]
-
A.
surfaceBrightness_V_mag_per_arcsec2
chosen
Indicates the surface brightness of an object measured in V-band magnitudes per square arcsecond, relating its emitted light to the area it covers on the sky.
-
B.
apparentBrightness
Indicates how bright one object appears from the perspective or location of another, regardless of its actual intrinsic luminosity.
-
C.
surfaceBrightnessClass
Indicates the qualitative classification of how bright an extended object (such as a galaxy) appears per unit area on the sky.
-
D.
intrinsicBrightness
Indicates the inherent level of light or luminosity an entity possesses, independent of external factors or observation conditions.
-
E.
surfaceBrightnessProfile
Indicates the distribution of brightness as a function of position across a surface, typically describing how intensity changes from one region to another.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b1159a888190aabb5c2a9268bd06 |
completed | April 22, 2026, 11:29 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:13 p.m.