Triple
T6010411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V0 detector |
E133816
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | particle physics detector sub-system |
C2616
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: particle physics detector sub-system Context triple: [V0 detector, instanceOf, particle physics detector sub-system]
-
A.
particle detector
chosen
A particle detector is a device or system that identifies, tracks, and measures properties of subatomic particles produced in physical processes or experiments.
-
B.
CERN accelerator complex component
A CERN accelerator complex component is a specialized physical or control-system element—such as magnets, RF cavities, beamlines, detectors, or power and cooling infrastructure—that collectively enables the production, acceleration, steering, and monitoring of particle beams for experimental research.
-
C.
particle physics experiment program
A particle physics experiment program is a coordinated set of software tools, data acquisition systems, and analysis workflows designed to plan, run, and interpret high-energy physics experiments.
-
D.
neutrino detector
A neutrino detector is a highly sensitive instrument or facility designed to observe and measure elusive neutrinos by capturing their rare interactions with matter, often deep underground or underwater to shield from background radiation.
-
E.
particle accelerator
A particle accelerator is a machine that uses electromagnetic fields to propel charged particles to high speeds and direct them into beams for research, medical, or industrial applications.
- F. None of above.
Provenance (1 batch)
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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
Created at: March 22, 2026, 4:06 p.m.