Silicon Strip Detector
E134965
A Silicon Strip Detector is a type of semiconductor particle detector that uses parallel strips of silicon to precisely measure the position and trajectory of charged particles in high-energy physics experiments.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Silicon Strip Detector canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1161191 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silicon Strip Detector Context triple: [Inner Tracking System, hasComponent, Silicon Strip Detector]
-
A.
Silicon Pixel Detector
The Silicon Pixel Detector is a high-precision tracking device in particle physics experiments that uses finely segmented silicon sensors to measure charged particle trajectories close to the interaction point.
-
B.
Silicon Drift Detector
A Silicon Drift Detector is a type of semiconductor radiation detector that uses lateral electric fields to drift charge carriers to a small collecting anode, enabling high energy resolution and fast, low-noise signal readout in applications such as particle tracking and X-ray spectroscopy.
-
C.
Time Projection Chamber
The Time Projection Chamber is a large gaseous detector used in particle physics experiments to track and identify charged particles in three dimensions with high precision.
-
D.
Electromagnetic Calorimeter
The Electromagnetic Calorimeter is a high-precision detector subsystem used in particle physics experiments to measure the energy and position of electrons and photons produced in high-energy collisions.
-
E.
RICH detector
The RICH detector is a ring-imaging Cherenkov device used in the NA62 experiment at CERN to identify charged particles by measuring the Cherenkov light they emit.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Silicon Strip Detector Target entity description: A Silicon Strip Detector is a type of semiconductor particle detector that uses parallel strips of silicon to precisely measure the position and trajectory of charged particles in high-energy physics experiments.
-
A.
Silicon Pixel Detector
The Silicon Pixel Detector is a high-precision tracking device in particle physics experiments that uses finely segmented silicon sensors to measure charged particle trajectories close to the interaction point.
-
B.
Silicon Drift Detector
A Silicon Drift Detector is a type of semiconductor radiation detector that uses lateral electric fields to drift charge carriers to a small collecting anode, enabling high energy resolution and fast, low-noise signal readout in applications such as particle tracking and X-ray spectroscopy.
-
C.
Time Projection Chamber
The Time Projection Chamber is a large gaseous detector used in particle physics experiments to track and identify charged particles in three dimensions with high precision.
-
D.
Electromagnetic Calorimeter
The Electromagnetic Calorimeter is a high-precision detector subsystem used in particle physics experiments to measure the energy and position of electrons and photons produced in high-energy collisions.
-
E.
RICH detector
The RICH detector is a ring-imaging Cherenkov device used in the NA62 experiment at CERN to identify charged particles by measuring the Cherenkov light they emit.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
position-sensitive detector
ⓘ
semiconductor particle detector ⓘ |
| advantage |
better timing than many gaseous detectors
ⓘ
higher granularity than many gaseous detectors ⓘ |
| advantageOver | gaseous wire chambers ⓘ |
| application |
beam monitoring
ⓘ
medical imaging research ⓘ nuclear physics experiments ⓘ tracking of charged particles ⓘ vertexing in collider detectors ⓘ |
| basedOn |
p-n junction
ⓘ
semiconductor diode ⓘ |
| detects | charged particles ⓘ |
| enables |
momentum measurement with magnetic field
ⓘ
precision vertex reconstruction ⓘ two-dimensional position measurement ⓘ |
| hasComponent | parallel silicon strips ⓘ |
| hasProperty |
fast response time
ⓘ
good signal-to-noise ratio ⓘ high spatial resolution ⓘ radiation hardness ⓘ |
| hasVariant |
double-sided silicon strip detector
ⓘ
microstrip detector ⓘ single-sided silicon strip detector ⓘ |
| mayRequire | cooling system ⓘ |
| measures |
particle position
ⓘ
particle trajectory ⓘ |
| operatesIn | depletion region of silicon ⓘ |
| operatesWith | reverse bias voltage ⓘ |
| produces | electron-hole pairs ⓘ |
| readOutBy |
analog-to-digital converters
ⓘ
front-end electronics ⓘ preamplifiers ⓘ shaping amplifiers ⓘ |
| requires |
bias voltage supply
ⓘ
low-noise electronics ⓘ |
| signalGeneration | ionization by charged particles ⓘ |
| stripOrientation | can be orthogonal in double-sided detectors ⓘ |
| stripPitch | typically between 20 and 100 micrometers ⓘ |
| usedIn |
ATLAS
ⓘ
surface form:
ATLAS experiment
CMS experiment ⓘ LHC experiments ⓘ collider experiments ⓘ fixed-target experiments ⓘ high-energy physics experiments ⓘ particle tracking systems ⓘ tracking detectors ⓘ vertex detectors ⓘ |
| usesMaterial | silicon ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Silicon Strip Detector Description of subject: A Silicon Strip Detector is a type of semiconductor particle detector that uses parallel strips of silicon to precisely measure the position and trajectory of charged particles in high-energy physics experiments.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.