Triple
T4917289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NGC 224 |
E110378
|
entity |
| Predicate | surfaceBrightnessClass |
P60001
|
FINISHED |
| Object | II |
—
|
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: II | Statement: [NGC 224, surfaceBrightnessClass, II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surfaceBrightnessClass Context triple: [NGC 224, surfaceBrightnessClass, II]
-
A.
surfaceBrightnessProfile
Indicates the distribution of brightness as a function of position across a surface, typically describing how intensity changes from one region to another.
-
B.
apparentBrightness
Indicates how bright one object appears from the perspective or location of another, regardless of its actual intrinsic luminosity.
-
C.
illuminationCondition
Indicates the lighting or brightness conditions under which an event, observation, or interaction takes place.
-
D.
lightLevel
Indicates the intensity or amount of light present in a given context or environment.
-
E.
maximumBrightness
Indicates the highest level of brightness that an entity can reach or exhibit.
- F. None of above. chosen
Provenance (4 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_69bd44132b94819088522d92beaadc78 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6fa760448190946401b4b21ea8b7 |
completed | March 20, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3421588190ab08e92b9558042e |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd6e482984819087124216738f1e29 |
completed | March 20, 2026, 3:56 p.m. |
Created at: March 20, 2026, 1:29 p.m.