Triple
T21818812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beta Cephei |
E538669
|
entity |
| Predicate | hasTypicalEffectiveTemperatureRange |
P57025
|
FINISHED |
| Object | 18,000–30,000 K |
—
|
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: 18,000–30,000 K | Statement: [Beta Cephei, hasTypicalEffectiveTemperatureRange, 18,000–30,000 K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalEffectiveTemperatureRange Context triple: [Beta Cephei, hasTypicalEffectiveTemperatureRange, 18,000–30,000 K]
-
A.
hasEffectiveTemperature
chosen
Indicates that an entity (typically a star or other astronomical object) possesses a specific effective surface temperature characterizing its emitted radiation.
-
B.
hasLowerSurfaceTemperatureThan
Indicates that the surface temperature of one entity is lower than the surface temperature of another entity.
-
C.
hasAverageSurfaceTemperature
Indicates that an entity is associated with a specific mean value of its surface temperature over a defined period or condition.
-
D.
hasSpectralTypeRange
Indicates that an entity is associated with a specified range of spectral types rather than a single, discrete spectral classification.
-
E.
hasTemperatureCategory
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
- 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_69e0c475038c8190abb9b1a20eb8ff50 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07ccd0d908190a43af4fcc7d6ca03 |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:54 p.m.