Triple
T17426809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1998 KY26 |
E423757
|
entity |
| Predicate | lightcurveUsedToDetermine |
P51230
|
FINISHED |
| Object | rotation period |
—
|
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: rotation period | Statement: [1998 KY26, lightcurveUsedToDetermine, rotation period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightcurveUsedToDetermine Context triple: [1998 KY26, lightcurveUsedToDetermine, rotation period]
-
A.
lightcurveIndicates
chosen
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.
-
B.
hasLightcurveMeasurements
Indicates that an entity has associated lightcurve measurements, representing recorded variations in its brightness over time.
-
C.
lightcurveInterpretation
Indicates the inferred physical explanation or model derived from analyzing an object's observed light curve behavior.
-
D.
lightCurveBehavior
Indicates how the intensity or brightness of an object changes over time, typically as represented in its light curve.
-
E.
lightcurveAmplitude
Indicates the measured range of brightness variation of an object over time in its light curve.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e448fcbf54819091babed0b9b05716 |
completed | April 19, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69e3b030eac481909b8402719cc3102e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.