Semantic reasoner

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A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description logic language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including Pei Wang's non-axiomatic reasoning system,[1] and probabilistic logic networks.[2]

List of semantic reasoners[edit]

Existing semantic reasoners and related software:

Commercial software[edit]

  • Bossam (software), an RETE-based rule engine with native supports for reasoning over OWL ontologies, SWRL rules, and RuleML rules.
  • RacerPro
  • OntoBroker is an inference engine with native reasoning over F-Logic, ObjectLogic, RIF, and OWL. ([1], W3C-listed inference engine)

Free to use (Closed Source)[edit]

  • Cyc inference engine, a forward and backward chaining inference engine with numerous specialized modules for high-order logic. ([2] ResearchCyc) ([3] OpenCyc)
  • KAON2 is an infrastructure for managing OWL-DL, SWRL, and F-Logic ontologies.
  • Internet Business Logic (software)—A reasoner designed for end-user app authors. Automatically generates and runs complex networked SQL queries. Explains the results in English at the end-user level.

Free software (open source)[edit]

  • Cwm, a forward-chaining reasoner used for querying, checking, transforming and filtering information. Its core language is RDF, extended to include rules, and it uses RDF/XML or N3 serializations as required. (CWM, W3C software license)
  • Drools, a forward-chaining inference-based rules engine which uses an enhanced implementation of the Rete algorithm. (Drools, Apache license 2.0)
  • OpenRules, an open source business rules and decision management system. Along with a sequential rule engine, includes an inferential rule engine that utilizes a constraint solver (OpenRules)
  • FaCT++ Reasoner, a tableaux-based reasoner for expressive Description Logics (DL), covering OWL and OWL 2 but lacking support for key constraints and some datatypes. Written in C++. (LGPL)
  • Flora-2, an object-oriented, rule-based knowledge-representation and reasoning system. (Flora-2, Apache 2.0)
  • Gandalf, open-source decision rules engine on PHP (GPL).
  • Prova, a semantic-web rule engine which supports data integration via SPARQL queries and type systems (RDFS, OWL ontologies as type system). (Prova, GNU GPL v2, commercial option available)
  • Pellet, OWL 2 DL reasoner (AGPL, commercial option available)
  • HermiT, OWL 2 DL reasoner (LGPL)
  • ELK, OWL 2 EL reasoner (Apache 2)
  • CEL, OWL 2 EL reasoner (Apache 2)
  • jcel, OWL 2 EL reasoner (LGPL / Apache 2)
  • RACER, OWL 2 DL reasoner (BSD-3)
  • Jena (framework), an open-source semantic-web framework for Java which includes a number of different semantic-reasoning modules. (Apache Jena, Apache License 2.0)
  • RDFSharp, an open source semantic web framework for .NET which includes a semantic extension implementing RDFS/OWL-DL/custom rule-based reasoning. (RDFSharp, Apache License 2.0)

Applications that contain reasoners[edit]

  • SemanticMiner includes the OntoBroker reasoner to perform ontology-based semantic search. [4]
  • SemanticGuide is an OntoBroker based expert system. [5]
  • Apache Marmotta includes a rule-based reasoner in its KiWi triple store.
  • dot15926 Editor—Ontology management framework initially designed for engineering ontology standard ISO 15926. Allows Python rule scripting and pattern-based data analysis. Supports extensions.

See also[edit]


  1. ^ Wang, Pei. "Grounded on Experience Semantics for intelligence, Tech report 96". CRCC. Retrieved 13 April 2015.  External link in |website= (help)
  2. ^ Goertzel, Ben; Iklé, Matthew; Goertzel, Izabela Freire; Heljakka, Ari (2008). Probabilistic Logic Networks: A Comprehensive Framework for Uncertain Inference. Springer Science & Business Media. p. 42. ISBN 9780387768724. 

External links[edit]