• Facets (new session)
• Description
• Metadata
• Settings
  • Rule: ActivityStreamsMapasEquivalentb3sb3sifpdbprdf-labelfacetshttp://dbpedia.org/resource/inference/rules/dbpedia#http://dbpedia.org/resource/inference/rules/opencyc#http://dbpedia.org/resource/inference/rules/umbel#http://dbpedia.org/resource/inference/rules/yago#http://dbpedia.org/schema/property_rules#http://www.ontologyportal.org/inference/rules/SUMO#http://www.ontologyportal.org/inference/rules/WordNet#http://www.w3.org/2002/07/owl#ldpoplwebskos-transurn:det:rdf:labelvirtrdf-labelvirtrdf-urlNone
    
  • Inverse Functional Properties: Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects
  • "Same As": Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects (recommended) Apply to subjects, objects and predicates (not recommended on big datasets) Apply to predicates only (special use cases only)

About: TRE (computing)     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : yago:WikicatRegularExpressions, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)

Type: Thingsoftwareschema:CreativeWorkworkwikidata:Q386724Softwareyago:Abstraction100002137yago:Appearance104673965yago:Attribute100024264yago:Code106355894yago:CodingSystem106353757yago:Communication100033020yago:Countenance104679549yago:Expression104679738yago:Quality104723816yago:Writing106359877yago:WrittenCommunication106349220libraryyago:Software106566077yago:WikicatRegularExpressions New Facet based on Instances of this Class

TRE is an open-source library for pattern matching in text, which works like a regular expression engine with the ability to do approximate string matching. It was developed by Ville Laurikari and is distributed under a 2-clause BSD-like license. The library is written in C and provides functions which allow using regular expressions for searching over input text lines. The main difference from other regular expression engines is that TRE can match text fragments in an approximate way, that is, supposing that text could have some number of typos.