Colander
E552007
Colander is a Python library used for data validation and deserialization, often employed in web applications to ensure structured and reliable input handling.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Colander canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T5838688 — 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: Colander Context triple: [Pylons Project, develops, Colander]
-
A.
Coltellini
Coltellini was an 18th-century Italian publisher and intellectual known for disseminating influential Enlightenment works, including Cesare Beccaria’s "Dei delitti e delle pene."
-
B.
Acciaroli
Acciaroli is a coastal village in southern Italy’s Cilento region, known for its picturesque harbor, beaches, and unusually high number of long-lived residents.
-
C.
Comer
Comer is a surname most prominently associated with English actress Jodie Comer, known for her acclaimed role in the television series "Killing Eve."
-
D.
Tarro
Tarro is a suburban railway station in the Hunter Region of New South Wales, Australia, serving the local community on the Main Northern line.
-
E.
Farino
Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
- 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: Colander Target entity description: Colander is a Python library used for data validation and deserialization, often employed in web applications to ensure structured and reliable input handling.
-
A.
Coltellini
Coltellini was an 18th-century Italian publisher and intellectual known for disseminating influential Enlightenment works, including Cesare Beccaria’s "Dei delitti e delle pene."
-
B.
Acciaroli
Acciaroli is a coastal village in southern Italy’s Cilento region, known for its picturesque harbor, beaches, and unusually high number of long-lived residents.
-
C.
Comer
Comer is a surname most prominently associated with English actress Jodie Comer, known for her acclaimed role in the television series "Killing Eve."
-
D.
Tarro
Tarro is a suburban railway station in the Hunter Region of New South Wales, Australia, serving the local community on the Main Northern line.
-
E.
Farino
Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
Python library
ⓘ
data validation library ⓘ deserialization library ⓘ |
| category |
Python data validation tool
ⓘ
Python web development tool ⓘ |
| commonlyUsedWith |
Pyramid web framework
NERFINISHED
ⓘ
web applications ⓘ |
| designGoal |
clear error reporting
ⓘ
reliable input handling ⓘ structured data validation ⓘ |
| documentationFormat | Sphinx-based documentation ⓘ |
| hasConcept |
Deserialization
ⓘ
Node ⓘ Schema ⓘ Serialization ⓘ Validator ⓘ |
| hasFeature |
choice validation
ⓘ
custom type definitions ⓘ localization of error messages ⓘ mapping schemas ⓘ range validation ⓘ regular expression validation ⓘ schema nodes for different data types ⓘ sequence schemas ⓘ string length validation ⓘ |
| license | BSD-like license ⓘ |
| outputFormat | Python native data structures ⓘ |
| programmingLanguage | Python ⓘ |
| repositoryPlatform | GitHub NERFINISHED ⓘ |
| supports |
custom validators
ⓘ
data coercion ⓘ data deserialization ⓘ data serialization ⓘ declarative schema definitions ⓘ default values ⓘ error reporting ⓘ nested schemas ⓘ required and optional fields ⓘ type conversion ⓘ |
| typicalInputFormat |
JSON-like structures
ⓘ
Python dictionaries ⓘ |
| usedFor |
data deserialization
ⓘ
data validation ⓘ form and JSON validation ⓘ input validation in web applications ⓘ schema-based validation ⓘ structured input handling ⓘ |
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: Colander Description of subject: Colander is a Python library used for data validation and deserialization, often employed in web applications to ensure structured and reliable input handling.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.