Triple

T15581898
Position Surface form Disambiguated ID Type / Status
Subject Type Ia supernovae E374518 entity
Predicate lightCurveFeature P51230 FINISHED
Object correlation between decline rate and peak luminosity 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: correlation between decline rate and peak luminosity | Statement: [Type Ia supernovae, lightCurveFeature, correlation between decline rate and peak luminosity]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: lightCurveFeature
Context triple: [Type Ia supernovae, lightCurveFeature, correlation between decline rate and peak luminosity]
  • A. lightcurveAmplitude
    Indicates the measured range of brightness variation of an object over time in its light curve.
  • B. 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.
  • C. lightcurveInterpretation
    Indicates the inferred physical explanation or model derived from analyzing an object's observed light curve behavior.
  • D. hasLightcurveAmplitude
    Indicates the measured range of brightness variation (amplitude) in an object's lightcurve over time.
  • E. hasLightcurveMeasurements
    Indicates that an entity has associated lightcurve measurements, representing recorded variations in its brightness 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e45ee3c8190a6aee06a5805ca39 completed April 16, 2026, 2:49 a.m.
PD Predicate disambiguation batch_69deda817e9881909b0c66fc9056f7d5 completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:11 a.m.