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020 _a9783642144189
_9978-3-642-14418-9
024 7 _a10.1007/978-3-642-14418-9
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aControlled Natural Language
_h[electronic resource] :
_bWorkshop on Controlled Natural Language, CNL 2009, Marettimo Island, Italy, June 8-10, 2009, Revised Papers /
_cedited by Norbert E Fuchs.
250 _a1st ed. 2010.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2010.
300 _aX, 291 p. 62 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v5972
505 0 _aLanguage Aspects -- An Evaluation Framework for Controlled Natural Languages -- Rhetorical Compositions for Controlled Natural Languages -- Anaphora Resolution Involving Interactive Knowledge Acquisition -- Talking Rabbit: A User Evaluation of Sentence Production -- Naturalness vs. Predictability: A Key Debate in Controlled Languages -- Implementing Controlled Languages in GF -- Polysemy in Controlled Natural Language Texts -- Economical Discourse Representation Theory -- Controlled English Ontology-Based Data Access -- SBVR’s Approach to Controlled Natural Language -- Tools and Applications -- The Naproche Project Controlled Natural Language Proof Checking of Mathematical Texts -- On Designing Controlled Natural Languages for Semantic Annotation -- Development of a Controlled Natural Language Interface for Semantic MediaWiki -- A Controlled Language for the Specification of Contracts -- Rabbit to OWL: Ontology Authoring with a CNL-Based Tool -- Writing Clinical Practice Guidelines in Controlled Natural Language -- What Are Controlled Natural Languages? -- On Controlled Natural Languages: Properties and Prospects.
520 _aControlled natural languages (CNLs) are subsets of natural languages, obtained by - stricting the grammar and vocabulary in order to reduce or eliminate ambiguity and complexity. Traditionally, controlled languagesfall into two major types: those that - prove readability for human readers, and those that enable reliable automatic semantic analysis of the language. [. . . ] The second type of languages has a formal logical basis, i. e. they have a formal syntax and semantics, and can be mapped to an existing formal language, such as ?rst-order logic. Thus, those languages can be used as knowledge representation languages, and writing of those languages is supported by fully au- matic consistency and redundancy checks, query answering, etc. Wikipedia Variouscontrollednatural languagesof the second type have been developedby a n- ber of organizations, and have been used in many different application domains, most recently within the Semantic Web. The workshop CNL 2009 was dedicated to discussing the similarities and the d- ferences of existing controlled natural languages of the second type, possible impro- ments to these languages, relations to other knowledge representation languages, tool support, existing and future applications, and further topics of interest.
650 0 _aArtificial intelligence.
650 0 _aCompilers (Computer programs).
650 0 _aData mining.
650 0 _aInformation storage and retrieval systems.
650 0 _aApplication software.
650 0 _aMachine theory.
650 1 4 _aArtificial Intelligence.
650 2 4 _aCompilers and Interpreters.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aFormal Languages and Automata Theory.
700 1 _aFuchs, Norbert E.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783642144172
776 0 8 _iPrinted edition:
_z9783642144196
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v5972
856 4 0 _uhttps://doi.org/10.1007/978-3-642-14418-9
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