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Semantic Analysis of Natural Language and Definite Clause Grammar using Statistical Parsing and Thesauri
Mälardalen University, School of Innovation, Design and Engineering.
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Services that rely on the semantic computations of users’ natural linguistic inputs are becoming more frequent. Computing semantic relatedness between texts is problematic due to the inherit ambiguity of natural language. The purpose of this thesis was to show how a sentence could be compared to a predefined semantic Definite Clause Grammar (DCG). Furthermore, it should show how a DCG-based system could benefit from such capabilities.

Our approach combines openly available specialized NLP frameworks for statistical parsing, part-of-speech tagging and word-sense disambiguation. We compute the semantic relatedness using a large lexical and conceptual-semantic thesaurus. Also, we extend an existing programming language for multimodal interfaces, which uses static predefined DCGs: COactive Language Definition (COLD). That is, every word that should be acceptable by COLD needs to be explicitly defined. By applying our solution, we show how our approach can remove dependencies on word definitions and improve grammar definitions in DCG-based systems.

Place, publisher, year, edition, pages
2013. , 27 p.
Keyword [en]
COLD, WordNet, thesaurus, semantic analysis, NLP, natural language processing, DFG, definite clause grammar, semantic relatedness
National Category
Computer Science
Identifiers
URN: urn:nbn:se:mdh:diva-26142OAI: oai:DiVA.org:mdh-26142DiVA: diva2:757050
Subject / course
Computer Science
Available from: 2014-10-27 Created: 2014-10-20 Last updated: 2014-10-27Bibliographically approved

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Computer Science

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
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  • Other locale
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Output format
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