ShEx
E664417
ShEx (Shape Expressions) is a concise, formal language for describing and validating the structure of RDF data graphs.
All labels observed (3)
How this entity was disambiguated
This entity first appeared as the object of triple T7423374 — 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: ShEx Context triple: [SHACL, relatedTo, ShEx]
-
A.
SHACL
SHACL is a W3C standard language for validating RDF data against a set of constraints or shapes.
-
B.
OWL 2 Manchester syntax
OWL 2 Manchester syntax is a user-friendly, human-readable syntax for writing OWL 2 ontologies, designed to be easier to read and write than XML- or logic-based notations.
-
C.
OWL 2 functional-style syntax
OWL 2 functional-style syntax is a formal, logic-oriented textual notation for writing OWL 2 ontologies in a precise and machine-readable way.
-
D.
Schematron
Schematron is a rule-based XML schema language that uses XPath expressions to define and validate complex structural and business constraints in XML documents.
-
E.
OWL 2 QL
OWL 2 QL is a lightweight profile of the Web Ontology Language designed to enable efficient query answering over large datasets using standard relational database technologies.
- 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: ShEx Target entity description: ShEx (Shape Expressions) is a concise, formal language for describing and validating the structure of RDF data graphs.
-
A.
SHACL
SHACL is a W3C standard language for validating RDF data against a set of constraints or shapes.
-
B.
OWL 2 Manchester syntax
OWL 2 Manchester syntax is a user-friendly, human-readable syntax for writing OWL 2 ontologies, designed to be easier to read and write than XML- or logic-based notations.
-
C.
OWL 2 functional-style syntax
OWL 2 functional-style syntax is a formal, logic-oriented textual notation for writing OWL 2 ontologies in a precise and machine-readable way.
-
D.
Schematron
Schematron is a rule-based XML schema language that uses XPath expressions to define and validate complex structural and business constraints in XML documents.
-
E.
OWL 2 QL
OWL 2 QL is a lightweight profile of the Web Ontology Language designed to enable efficient query answering over large datasets using standard relational database technologies.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
RDF validation language
ⓘ
constraint language ⓘ shape expression language ⓘ |
| alternativeTo | SHACL ⓘ |
| appliesTo |
API input validation for RDF-based systems
ⓘ
RDF data validation ⓘ data quality checking ⓘ schema-driven RDF data design ⓘ |
| comparedWith | SHACL ⓘ |
| describes | RDF graph structure ⓘ |
| domain |
Linked Data
ⓘ
Semantic Web ⓘ |
| fullName | Shape Expressions ⓘ |
| hasAbbreviation | ShEx ⓘ |
| hasConcept |
node constraint
ⓘ
shape ⓘ shape map ⓘ triple constraint ⓘ value class ⓘ |
| hasFeature |
annotations on shapes and triple constraints
ⓘ
closed and open shapes ⓘ concise syntax ⓘ formal semantics ⓘ human-readable syntax ⓘ imports of external schemas ⓘ support for RDF node constraints ⓘ support for cardinality constraints ⓘ support for grouping and choice of properties ⓘ support for negation of shapes ⓘ support for recursion ⓘ support for value constraints ⓘ |
| hasSerialization |
ShExC
ⓘ
linked to:
ShEx
ShExJ ⓘ
linked to:
ShEx
ShExR ⓘ |
| supports |
RDF IRIs
ⓘ
RDF blank nodes ⓘ RDF datatypes ⓘ RDF literals ⓘ RDF node kinds ⓘ regular-expression-like expressions over triples ⓘ shape references ⓘ value sets ⓘ |
| syntaxStyle |
JSON-based syntax
ⓘ
RDF-based syntax ⓘ compact text syntax ⓘ |
| usedFor |
defining constraints on RDF data
ⓘ
validating RDF data graphs ⓘ |
| usedIn |
Wikidata data modeling
ⓘ
knowledge graph validation ⓘ |
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: ShEx Description of subject: ShEx (Shape Expressions) is a concise, formal language for describing and validating the structure of RDF data graphs.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: ShEx
linked to: ShEx