Triple

T24435743
Position Surface form Disambiguated ID Type / Status
Subject SwissFEL E616119 entity
Predicate photonEnergyRange P1457 FINISHED
Object soft X-ray to hard X-ray range 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: soft X-ray to hard X-ray range | Statement: [SwissFEL, photonEnergyRange, soft X-ray to hard X-ray range]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: photonEnergyRange
Context triple: [SwissFEL, photonEnergyRange, soft X-ray to hard X-ray range]
  • A. energyRangeUpperBound_MeV
    Indicates the maximum energy value, expressed in mega–electronvolts (MeV), that defines the upper limit of an energy range in the relationship.
  • B. typicalEnergyRange chosen
    Indicates the usual or characteristic range of energy values associated with an entity, process, or interaction.
  • C. energyRangeLowerBound_keV
    Indicates the minimum energy value, in kilo–electron volts (keV), that defines the lower limit of an energy range for the relationship or measurement.
  • D. electronEnergy
    Indicates the amount of energy associated with an electron in a given state, configuration, or context.
  • E. approximateWavelengthRange
    Indicates the range of wavelengths that approximately characterizes or bounds the phenomenon, object, or interaction in question.
  • 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_69e2d7ec44b081909ccaf1f3bbec0641 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f2978638888190aef3ab5fc8bf0ed4 completed April 29, 2026, 11:43 p.m.
PD Predicate disambiguation batch_69f287d3237c819099559c00f83131d8 completed April 29, 2026, 10:36 p.m.
Created at: April 18, 2026, 2:16 a.m.