Triple
T22695478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMS silicon pixel detector |
E561161
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | silicon pixel tracking detector |
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: silicon pixel tracking detector Context triple: [CMS silicon pixel detector, instanceOf, silicon pixel tracking detector]
-
A.
particle detector design
Particle detector design is the conceptual process of specifying and optimizing the geometry, materials, and readout systems of a detector to accurately measure and identify particles produced in physical interactions.
-
B.
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.
-
C.
X-ray detector system
An X-ray detector system is an integrated assembly of sensors, electronics, and processing components that captures incoming X-ray radiation and converts it into usable digital images or measurement data for analysis and diagnostics.
-
D.
large-acceptance spectrometer
A large-acceptance spectrometer is an instrument designed to detect and analyze particles or radiation over a wide range of angles and momenta simultaneously, enabling efficient collection of comprehensive experimental data.
-
E.
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.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
Created at: April 17, 2026, 3:14 p.m.