NetworkX
E459727
NetworkX is a Python library for creating, analyzing, and visualizing complex networks and graphs.
All labels observed (1)
| Label | Occurrences |
|---|---|
| NetworkX canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4599960 — 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: NetworkX Context triple: [Python scientific stack, hasComponent, NetworkX]
-
A.
DGL
DGL is the vehicle registration code assigned to the town of Głogów in Poland.
-
B.
Matplotlib
Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
-
C.
Seaborn
Seaborn is a Python data visualization library built on top of Matplotlib that provides a high-level interface for creating attractive and informative statistical graphics.
-
D.
Seaborn
Seaborn is a masculine given name of English origin, historically used in colonial America and associated with individuals such as Seaborn Cotton.
-
E.
Canvas Network
Canvas Network is an online learning platform that hosts and delivers massive open online courses (MOOCs) from universities and institutions worldwide.
- 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: NetworkX Target entity description: NetworkX is a Python library for creating, analyzing, and visualizing complex networks and graphs.
-
A.
DGL
DGL is the vehicle registration code assigned to the town of Głogów in Poland.
-
B.
Matplotlib
Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
-
C.
Seaborn
Seaborn is a Python data visualization library built on top of Matplotlib that provides a high-level interface for creating attractive and informative statistical graphics.
-
D.
Seaborn
Seaborn is a masculine given name of English origin, historically used in colonial America and associated with individuals such as Seaborn Cotton.
-
E.
Canvas Network
Canvas Network is an online learning platform that hosts and delivers massive open online courses (MOOCs) from universities and institutions worldwide.
- F. None of above. chosen
Statements (51)
| Predicate | Object |
|---|---|
| instanceOf |
Python library
ⓘ
graph theory software ⓘ open-source software ⓘ |
| documentationUrl | https://networkx.org/documentation/stable/ ⓘ |
| hasFeature |
algorithms implemented as functions
ⓘ
attribute support for nodes and edges ⓘ extensible data structures ⓘ integration with Matplotlib ⓘ integration with NumPy ⓘ integration with SciPy ⓘ iterators for nodes and edges ⓘ pure Python implementation ⓘ read and write support for multiple graph formats ⓘ support for dense graphs ⓘ support for sparse graphs ⓘ |
| hasHomepage | https://networkx.org/ ⓘ |
| importName | networkx NERFINISHED ⓘ |
| license | BSD license NERFINISHED ⓘ |
| maintainedBy | NetworkX developers community ⓘ |
| programmingLanguage | Python ⓘ |
| repositoryPlatform | GitHub NERFINISHED ⓘ |
| supports |
bipartite graphs
ⓘ
centrality measures ⓘ clustering algorithms ⓘ community detection utilities ⓘ complex networks ⓘ connectivity analysis ⓘ degree distribution analysis ⓘ directed graphs ⓘ flow algorithms ⓘ graph algorithms ⓘ graph analysis ⓘ graph creation ⓘ graph drawing ⓘ graph traversal ⓘ graph visualization ⓘ isomorphism checking ⓘ multigraphs ⓘ random graph generation ⓘ shortest path algorithms ⓘ undirected graphs ⓘ unweighted graphs ⓘ weighted graphs ⓘ |
| usedFor |
biological network analysis
ⓘ
education in graph theory ⓘ information network analysis ⓘ infrastructure network modeling ⓘ network science research ⓘ prototyping graph algorithms ⓘ social network analysis ⓘ |
| writtenIn | Python ⓘ |
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: NetworkX Description of subject: NetworkX is a Python library for creating, analyzing, and visualizing complex networks and graphs.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.