ROOT
E134370
ROOT is a widely used object-oriented data analysis framework and file format developed at CERN for storing, processing, and visualizing large volumes of high-energy physics data.
All labels observed (4)
| Label | Occurrences |
|---|---|
| RDataFrame | 1 |
| ROOT canonical | 1 |
| ROOT I/O | 1 |
| ROOT graphics | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1166278 — 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: ROOT Context triple: [CMS experiment, dataFormat, ROOT]
-
A.
NA62
NA62 is a high-energy physics experiment at CERN designed primarily to study rare kaon decays and test the predictions of the Standard Model.
-
B.
CACTUS
CACTUS is the former air traffic control callsign used by US Airways for its flight operations.
-
C.
NA61/SHINE
NA61/SHINE is a fixed-target experiment at CERN that studies hadron production and properties of strongly interacting matter using high-energy beams from the Super Proton Synchrotron.
-
D.
ATLAS
ATLAS is a major particle physics experiment and detector at the Large Hadron Collider that investigates fundamental particles and forces, including the Higgs boson.
-
E.
DØ detector
The DØ detector is a large particle physics experiment at Fermilab’s Tevatron collider designed to study high-energy proton–antiproton collisions and probe fundamental particles and forces.
- 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: ROOT Target entity description: ROOT is a widely used object-oriented data analysis framework and file format developed at CERN for storing, processing, and visualizing large volumes of high-energy physics data.
-
A.
NA62
NA62 is a high-energy physics experiment at CERN designed primarily to study rare kaon decays and test the predictions of the Standard Model.
-
B.
CACTUS
CACTUS is the former air traffic control callsign used by US Airways for its flight operations.
-
C.
T2K
T2K is a long-baseline neutrino oscillation experiment in Japan that studies how neutrinos change type as they travel from J-PARC to the Super-Kamiokande detector.
-
D.
NA61/SHINE
NA61/SHINE is a fixed-target experiment at CERN that studies hadron production and properties of strongly interacting matter using high-energy beams from the Super Proton Synchrotron.
-
E.
ATLAS
ATLAS is a major particle physics experiment and detector at the Large Hadron Collider that investigates fundamental particles and forces, including the Higgs boson.
- F. None of above. chosen
Statements (51)
| Predicate | Object |
|---|---|
| instanceOf |
data analysis framework
ⓘ
file format ⓘ object-oriented software framework ⓘ scientific software ⓘ |
| developer | CERN ⓘ |
| domain |
astroparticle physics
ⓘ
high-energy physics ⓘ nuclear physics ⓘ |
| fileExtension | .root ⓘ |
| hasComponent |
Cling
ⓘ
Math libraries ⓘ PROOF ⓘ RDataFrame ⓘ
linked to:
ROOT
ROOT I/O ⓘ
linked to:
ROOT
ROOT graphics ⓘ
linked to:
ROOT
TCanvas ⓘ TFile ⓘ TGraph ⓘ TH1 ⓘ TMVA ⓘ TTree ⓘ |
| license |
LGPL
ⓘ
linked to:
GNU Lesser General Public License
|
| openSource | true ⓘ |
| origin | CERN computing group ⓘ |
| programmingLanguage | C++ ⓘ |
| supports |
C++ interpreter
ⓘ
Python bindings ⓘ batch processing ⓘ columnar data storage ⓘ compression ⓘ interactive analysis ⓘ multithreading ⓘ parallel processing ⓘ |
| supportsLanguage |
C++
ⓘ
Julia ⓘ Python ⓘ R ⓘ |
| usedBy |
ALICE collaboration
ⓘ
linked to:
ALICE experiment
ATLAS collaboration ⓘ
linked to:
ATLAS
CMS collaboration ⓘ
linked to:
CMS Collaboration
LHC experiments ⓘ LHCb collaboration ⓘ
linked to:
LHCb
|
| usedFor |
data processing
ⓘ
data storage ⓘ data visualization ⓘ event display ⓘ fitting ⓘ high-energy physics data analysis ⓘ histogramming ⓘ machine learning ⓘ statistical analysis ⓘ |
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: ROOT Description of subject: ROOT is a widely used object-oriented data analysis framework and file format developed at CERN for storing, processing, and visualizing large volumes of high-energy physics data.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: ROOT
linked to: ROOT
linked to: ROOT