Triple
T1184052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CNGS |
E25204
|
entity |
| Predicate | neutrinoEnergyRange |
P1457
|
FINISHED |
| Object | tens of GeV |
—
|
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: tens of GeV | Statement: [CNGS, neutrinoEnergyRange, tens of GeV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neutrinoEnergyRange Context triple: [CNGS, neutrinoEnergyRange, tens of GeV]
-
A.
typicalEnergyRange
chosen
Indicates the usual or characteristic range of energy values associated with an entity, process, or interaction.
-
B.
maximumProtonEnergy
Indicates the highest energy value that protons can attain in a given system, process, or context.
-
C.
neutronSpectrum
Indicates the energy distribution or range of neutrons present in a given system, interaction, or environment.
-
D.
measuredNumberOfLightNeutrinoFamilies
Indicates the experimentally determined count of distinct light neutrino families inferred from measurements.
-
E.
beamEnergy
Indicates the amount of energy carried by or assigned to a beam in a physical or engineered system.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd37b4a88190bb71a2d272c5fd1a |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb59ca6c81908597a81646674aaa |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.