Triple
T21818829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beta Cephei |
E538669
|
entity |
| Predicate | hasTypicalRadialVelocityVariations |
P62576
|
FINISHED |
| Object | tens of km/s |
—
|
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: tens of km/s | Statement: [Beta Cephei, hasTypicalRadialVelocityVariations, tens of km/s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalRadialVelocityVariations Context triple: [Beta Cephei, hasTypicalRadialVelocityVariations, tens of km/s]
-
A.
hasRadialVelocityMeasurement
Indicates that a radial velocity value has been measured for an entity, typically quantifying its motion along the line of sight relative to an observer.
-
B.
hasRadialVelocity_km_per_s
Indicates that one entity has a measured radial velocity, expressed in kilometers per second, relative to another reference frame or object.
-
C.
hasRadialVelocitySignature
chosen
Indicates that an object exhibits a measurable radial velocity pattern characteristic of a specific physical process or source.
-
D.
hasLightcurveVariations
Indicates that an object exhibits measurable changes in its brightness over time, as captured in its lightcurve.
-
E.
radialVelocitySignalPeriodicity
Indicates that the radial velocity measurements of an object exhibit a repeating, periodic signal over time.
- 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.