Triple
T20326829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RR Lyrae variable star |
E492359
|
entity |
| Predicate | lightCurveShapeRRc |
P122576
|
FINISHED |
| Object | more sinusoidal |
—
|
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: more sinusoidal | Statement: [RR Lyrae variable star, lightCurveShapeRRc, more sinusoidal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightCurveShapeRRc Context triple: [RR Lyrae variable star, lightCurveShapeRRc, more sinusoidal]
-
A.
lightCurveType
Indicates the classification of how an object's brightness changes over time as represented by its light curve.
-
B.
lightcurveIndicates
Indicates that the characteristics or pattern of an object's light curve provide evidence for or reveal information about a particular property, state, or event associated with that object.
-
C.
lightCurveBehavior
chosen
Indicates how the intensity or brightness of an object changes over time, typically as represented in its light curve.
-
D.
lightcurveAmplitude
Indicates the measured range of brightness variation of an object over time in its light curve.
-
E.
lightcurveInterpretation
Indicates the inferred physical explanation or model derived from analyzing an object's observed light curve behavior.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677e4130081909ec54f131939e442 |
completed | April 20, 2026, 7 p.m. |
| PD | Predicate disambiguation | batch_69e5762655ac8190a8cc48a29fa2c0c4 |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:21 a.m.