Triple
T18776177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R Scuti |
E459138
|
entity |
| Predicate | minimumBrightnessRequiresBinoculars |
P69293
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [R Scuti, minimumBrightnessRequiresBinoculars, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumBrightnessRequiresBinoculars Context triple: [R Scuti, minimumBrightnessRequiresBinoculars, yes]
-
A.
visibleInBinoculars
chosen
Indicates that one entity can be seen through binoculars from the vantage point of another entity.
-
B.
visibleToNakedEye
Indicates that something can be perceived directly without the aid of optical instruments such as telescopes, microscopes, or binoculars.
-
C.
canBeSeenWith
Indicates that two entities are observable together in the same context, setting, or time.
-
D.
hasVeryLowSurfaceBrightness
Indicates that an entity exhibits an extremely faint or low level of brightness across its visible surface.
-
E.
hasNightVision
Indicates that an entity possesses the ability to see effectively in low-light or dark conditions.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5933b912481908bfd97216eacb257 |
completed | April 20, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69e48d1126e4819099607837ed5aadca |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.