Triple
T29768498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trumpler II 3 m |
E753981
|
entity |
| Predicate | brightnessRangeClass |
P167863
|
FINISHED |
| Object | m |
—
|
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: m | Statement: [Trumpler II 3 m, brightnessRangeClass, m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brightnessRangeClass Context triple: [Trumpler II 3 m, brightnessRangeClass, m]
-
A.
brightnessVariation
Indicates a change or fluctuation in the level of brightness of an entity over time or across conditions.
-
B.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
-
C.
surfaceBrightnessClass
Indicates the qualitative classification of how bright an extended object (such as a galaxy) appears per unit area on the sky.
-
D.
brightnessRole
Indicates a relationship where one entity serves a specific role in determining, controlling, or characterizing the brightness of another entity.
-
E.
brightnessCorrelatesWith
Indicates that changes in the brightness of one entity are systematically associated with changes in the brightness of another entity.
- 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_69f0ef827ff88190ade56e0b0846b713 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6745f8354819085a81de5c32dd49e |
completed | May 2, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 28, 2026, 8:40 p.m.