Streamlit
E97082
Streamlit is an open-source Python framework that lets developers quickly build and share interactive web apps for data science and machine learning.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Streamlit canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T816685 — 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: Streamlit Context triple: [Plotly, integratesWith, Streamlit]
-
A.
Plotly
Plotly is an interactive, open-source graphing and data visualization library widely used in Python for creating rich, web-based charts and dashboards.
-
B.
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.
-
C.
Flask
Flask is a minor but tough and pugnacious third mate aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
-
D.
Flask
Flask is a lightweight, flexible Python micro web framework designed for building web applications and APIs with minimal boilerplate.
-
E.
Data Studio
Data Studio is Google's free data visualization and business intelligence tool that lets users create interactive, shareable reports and dashboards from multiple data sources.
- 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: Streamlit Target entity description: Streamlit is an open-source Python framework that lets developers quickly build and share interactive web apps for data science and machine learning.
-
A.
Plotly
Plotly is an interactive, open-source graphing and data visualization library widely used in Python for creating rich, web-based charts and dashboards.
-
B.
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.
-
C.
Flask
Flask is a lightweight, flexible Python micro web framework designed for building web applications and APIs with minimal boilerplate.
-
D.
Flask
Flask is a minor but tough and pugnacious third mate aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
-
E.
Data Studio
Data Studio is Google's free data visualization and business intelligence tool that lets users create interactive, shareable reports and dashboards from multiple data sources.
- F. None of above. chosen
Statements (58)
| Predicate | Object |
|---|---|
| instanceOf |
Python library
ⓘ
open-source software framework ⓘ web application framework ⓘ |
| acquiredBy |
Snowflake Data Cloud
ⓘ
surface form:
Snowflake Inc.
|
| acquisitionAnnounced | 2022 ⓘ |
| deploymentOption |
Streamlit Community Cloud
ⓘ
deployment on cloud platforms ⓘ self-hosting on servers ⓘ |
| designGoal |
Python-first development
ⓘ
minimal boilerplate ⓘ rapid prototyping ⓘ simplicity ⓘ |
| documentation | https://docs.streamlit.io ⓘ |
| foundedBy |
Adrien Treuille
ⓘ
Amanda Kelly ⓘ Thiago Teixeira ⓘ |
| genre |
dashboarding framework
ⓘ
data science tool ⓘ machine learning tool ⓘ |
| hasFeature |
automatic UI generation from Python code
ⓘ
built-in web server ⓘ command-line interface ⓘ component system for custom JS components ⓘ declarative UI syntax ⓘ server-side execution ⓘ widget-based interaction model ⓘ |
| headquartersLocation | San Francisco ⓘ |
| initialReleaseYear | 2019 ⓘ |
| license | Apache License 2.0 ⓘ |
| programmingLanguage | Python ⓘ |
| repository | https://github.com/streamlit/streamlit ⓘ |
| supports |
Altair integration
ⓘ
Authentication via external tools ⓘ Bokeh integration ⓘ Mapbox maps ⓘ Markdown rendering ⓘ Matplotlib integration ⓘ Pandas DataFrame display ⓘ Plotly integration ⓘ Seaborn integration ⓘ Theming ⓘ caching of computations ⓘ data visualization ⓘ file upload ⓘ hot-reloading ⓘ interactive widgets ⓘ layout customization ⓘ session state ⓘ |
| targetUser |
Python developers
ⓘ
data scientists ⓘ machine learning engineers ⓘ |
| typicalCommand | streamlit run ⓘ |
| useCase |
building interactive web apps
ⓘ
data dashboards ⓘ data exploration ⓘ machine learning model demos ⓘ prototyping data apps ⓘ |
| website | https://streamlit.io ⓘ |
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: Streamlit Description of subject: Streamlit is an open-source Python framework that lets developers quickly build and share interactive web apps for data science and machine learning.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.