Triple
T20074556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omega laser system |
E499825
|
entity |
| Predicate | peakEnergyClass |
P48765
|
FINISHED |
| Object | kilojoule-class |
—
|
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: kilojoule-class | Statement: [Omega laser system, peakEnergyClass, kilojoule-class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakEnergyClass Context triple: [Omega laser system, peakEnergyClass, kilojoule-class]
-
A.
energyEfficiencyClass
Indicates the energy efficiency rating category assigned to an item, typically reflecting how efficiently it uses or conserves energy relative to defined standards.
-
B.
energyEfficiencyFeature
Indicates that an entity has a design, technology, or characteristic specifically intended to reduce energy consumption or improve energy performance.
-
C.
energyRegime
Indicates the specific range or mode of energy conditions under which a process, interaction, or system operates or is characterized.
-
D.
energyThroughputCategory
chosen
Indicates the classification of an entity based on the amount or level of energy it processes or transfers over a given period.
-
E.
designEnergy
Indicates that an entity is responsible for planning, specifying, or determining the energy-related characteristics or performance of another entity.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66439efe881909a068c3f05022421 |
completed | April 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.