sqlmodel
E426657
SQLModel is a Python library by Sebastián Ramírez (tiangolo) that combines SQLAlchemy and Pydantic to provide an easy, type-safe way to define and interact with SQL databases.
All labels observed (2)
How this entity was disambiguated
This entity first appeared as the object of triple T4276858 — 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: sqlmodel Context triple: [tiangolo, hostsProject, sqlmodel]
-
A.
Flask-SQLAlchemy
Flask-SQLAlchemy is a popular Flask extension that integrates the SQLAlchemy ORM with Flask applications to simplify database configuration and usage.
-
B.
DC ORM
DC ORM is the abbreviated name for the District of Columbia Office of Risk Management, the agency responsible for managing risk, insurance, and related claims for the D.C. government.
-
C.
SQL
SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
-
D.
SQLite
SQLite is a lightweight, self-contained, serverless SQL database engine widely embedded in applications, operating systems, and devices.
-
E.
Flask-Migrate
Flask-Migrate is a Flask extension that integrates Alembic-based database schema migrations into Flask applications.
- 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: sqlmodel Target entity description: SQLModel is a Python library by Sebastián Ramírez (tiangolo) that combines SQLAlchemy and Pydantic to provide an easy, type-safe way to define and interact with SQL databases.
-
A.
Flask-SQLAlchemy
Flask-SQLAlchemy is a popular Flask extension that integrates the SQLAlchemy ORM with Flask applications to simplify database configuration and usage.
-
B.
DC ORM
DC ORM is the abbreviated name for the District of Columbia Office of Risk Management, the agency responsible for managing risk, insurance, and related claims for the D.C. government.
-
C.
SQL
SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
-
D.
SQLite
SQLite is a lightweight, self-contained, serverless SQL database engine widely embedded in applications, operating systems, and devices.
-
E.
Flask-Migrate
Flask-Migrate is a Flask extension that integrates Alembic-based database schema migrations into Flask applications.
- F. None of above. chosen
Statements (63)
| Predicate | Object |
|---|---|
| instanceOf |
ORM toolkit
ⓘ
Python library ⓘ data modeling library ⓘ |
| basedOn |
Pydantic
ⓘ
SQLAlchemy ⓘ |
| compatibleWith |
FastAPI
ⓘ
Pydantic v1 ⓘ
linked to:
Pydantic
SQLAlchemy 1.4+ ⓘ
linked to:
SQLAlchemy
|
| creator |
Sebastián Ramírez
ⓘ
tiangolo ⓘ |
| designedFor |
integration with FastAPI
ⓘ
relational databases ⓘ type-safe database access ⓘ |
| documentationUrl | https://sqlmodel.tiangolo.com ⓘ |
| firstClassCitizenIn |
FastAPI ecosystem
ⓘ
linked to:
FastAPI
|
| hasFeature |
FastAPI-friendly models
ⓘ
Pydantic-compatible models ⓘ async session support ⓘ automatic OpenAPI schema compatibility ⓘ column type specification ⓘ declarative model definition ⓘ default values ⓘ nullable fields ⓘ primary key declaration ⓘ relationship loading ⓘ session dependency injection with FastAPI ⓘ type-safe queries ⓘ unique constraints ⓘ |
| hostedOn | GitHub ⓘ |
| license | MIT License ⓘ |
| programmingLanguage | Python ⓘ |
| repositoryOwner | tiangolo ⓘ |
| sourceCodeUrl | https://github.com/tiangolo/sqlmodel ⓘ |
| supports |
Alembic migrations
ⓘ
FastAPI integration ⓘ MariaDB ⓘ MySQL ⓘ ORM-style queries ⓘ PostgreSQL ⓘ Pydantic models ⓘ Python type annotations ⓘ SQL Server ⓘ SQLAlchemy Core ⓘ
linked to:
SQLAlchemy
SQLAlchemy ORM ⓘ
linked to:
SQLAlchemy
SQLAlchemy sessions ⓘ SQLite ⓘ asynchronous database operations ⓘ automatic table creation ⓘ constraints ⓘ data validation ⓘ deserialization ⓘ foreign keys ⓘ indexes ⓘ model inheritance ⓘ relationships ⓘ schema generation ⓘ serialization ⓘ synchronous database operations ⓘ type hints ⓘ |
| typicalUseCase |
building CRUD APIs
ⓘ
defining database models with type hints ⓘ prototyping database-backed applications ⓘ |
| 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: sqlmodel Description of subject: SQLModel is a Python library by Sebastián Ramírez (tiangolo) that combines SQLAlchemy and Pydantic to provide an easy, type-safe way to define and interact with SQL databases.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject linked to:
tiangolo organization on GitHub
subject linked to:
tiangolo organization on GitHub
linked to: sqlmodel
linked to: sqlmodel
linked to: sqlmodel
linked to: sqlmodel