The Description Logic Handbook
E1027658
The Description Logic Handbook is a comprehensive reference work on description logics, covering their theory, implementation, and applications in knowledge representation and reasoning.
All labels observed (1)
| Label | Occurrences |
|---|---|
| The Description Logic Handbook canonical | 3 |
How this entity was disambiguated
This entity first appeared as the object of triple T13193699 — 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: The Description Logic Handbook Context triple: [Ralf Baader, authorOf, The Description Logic Handbook]
-
A.
OWL 2 RL
OWL 2 RL is a profile of the Web Ontology Language designed for scalable reasoning using rule-based systems, enabling efficient inference over large datasets.
-
B.
OWL 2 EL
OWL 2 EL is a lightweight profile of the Web Ontology Language designed for efficient reasoning over large-scale ontologies, particularly in domains like biomedical terminologies.
-
C.
OWL 2 DL
OWL 2 DL is a highly expressive yet decidable description logic–based profile of the OWL 2 Web Ontology Language, designed to balance rich modeling capabilities with computational completeness and decidability.
-
D.
OWL 2 Full
OWL 2 Full is a highly expressive semantic web ontology language variant that fully integrates OWL with RDF, allowing powerful but undecidable reasoning over web data.
-
E.
OWL 2 Web Ontology Language
OWL 2 Web Ontology Language is a W3C-standardized knowledge representation language used to create, share, and reason over rich ontologies on the Semantic Web.
- 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: The Description Logic Handbook Target entity description: The Description Logic Handbook is a comprehensive reference work on description logics, covering their theory, implementation, and applications in knowledge representation and reasoning.
-
A.
OWL 2 RL
OWL 2 RL is a profile of the Web Ontology Language designed for scalable reasoning using rule-based systems, enabling efficient inference over large datasets.
-
B.
OWL 2 EL
OWL 2 EL is a lightweight profile of the Web Ontology Language designed for efficient reasoning over large-scale ontologies, particularly in domains like biomedical terminologies.
-
C.
OWL 2 DL
OWL 2 DL is a highly expressive yet decidable description logic–based profile of the OWL 2 Web Ontology Language, designed to balance rich modeling capabilities with computational completeness and decidability.
-
D.
OWL 2 Full
OWL 2 Full is a highly expressive semantic web ontology language variant that fully integrates OWL with RDF, allowing powerful but undecidable reasoning over web data.
-
E.
OWL 2 Web Ontology Language
OWL 2 Web Ontology Language is a W3C-standardized knowledge representation language used to create, share, and reason over rich ontologies on the Semantic Web.
- F. None of above. chosen
Statements (40)
| Predicate | Object |
|---|---|
| instanceOf |
book
ⓘ
reference work ⓘ |
| covers |
applications of description logics in knowledge-based systems
ⓘ
applications of description logics in ontologies ⓘ applications of description logics in the Semantic Web ⓘ complexity of description logics ⓘ implementation techniques for description logic systems ⓘ reasoning algorithms for description logics ⓘ semantics of description logics ⓘ syntax of description logics ⓘ |
| editor |
Daniele Nardi
NERFINISHED
ⓘ
Diego Calvanese NERFINISHED ⓘ Franz Baader NERFINISHED ⓘ Peter F. Patel-Schneider NERFINISHED ⓘ |
| field |
artificial intelligence
ⓘ
computer science ⓘ knowledge representation and reasoning ⓘ |
| focusesOn |
applications of description logics
ⓘ
implementation of description logics ⓘ theory of description logics ⓘ |
| hasEdition |
The Description Logic Handbook: Theory, Implementation, and Applications (first edition)
NERFINISHED
ⓘ
The Description Logic Handbook: Theory, Implementation, and Applications (second edition) NERFINISHED ⓘ |
| hasPart |
chapters on applications of description logics
ⓘ
chapters on basic description logics ⓘ chapters on expressive description logics ⓘ chapters on reasoning procedures ⓘ chapters on systems and tools for description logics ⓘ |
| intendedFor |
graduate students in computer science
ⓘ
practitioners building reasoning systems ⓘ researchers in knowledge representation ⓘ |
| isUsedAs | standard reference on description logics ⓘ |
| language | English ⓘ |
| publisher | Cambridge University Press ⓘ |
| relatedTo |
description logic reasoners
ⓘ
knowledge-based systems ⓘ ontology languages ⓘ |
| subject |
automated reasoning
ⓘ
description logics ⓘ knowledge representation ⓘ |
| title | The Description Logic Handbook NERFINISHED ⓘ |
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: The Description Logic Handbook Description of subject: The Description Logic Handbook is a comprehensive reference work on description logics, covering their theory, implementation, and applications in knowledge representation and reasoning.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.