Triple
T19260843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IMB |
E481645
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | underground water Cherenkov detector |
C1452
|
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: underground water Cherenkov detector Context triple: [IMB, instanceOf, underground water Cherenkov detector]
-
A.
neutrino detector
chosen
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.
-
B.
underwater detection system
An underwater detection system is a specialized arrangement of sensors, processing units, and communication components designed to identify, track, and analyze objects or phenomena beneath the water’s surface.
-
C.
long-baseline neutrino experiment
A long-baseline neutrino experiment is a particle physics setup in which a beam of neutrinos is produced at one location and detected hundreds to thousands of kilometers away to study neutrino oscillations and fundamental properties.
-
D.
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.
-
E.
particle detector
A particle detector is a device or system that identifies, tracks, and measures properties of subatomic particles produced in physical processes or experiments.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 1:28 p.m.