Two Experiments on Learning Probabilistic Dependency Grammars from Corpora
Two Experiments on Learning Probabilistic Dependency Grammars from Corpora
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In recent years, CNL (Controlled Natural Language) has received much attention with regard to ontology-based knowledge acquisition systems. CNLs, as subsets of natural languages, can be useful for both humans and computers by eliminating ambiguity of natural languages. Our previous work, OntoPath [10], proposed to edit natural language-like narratives that are structured in RDF (Resource Description Framework) triples, using a domain-specific ontology as their language constituents. However, our previous work and other systems employing CFG for grammar definition have difficulties in enlarging the expression capacity. A newly developed editor, which we propose in this paper, permits grammar definitions through CFG-LD (Context-Free Grammar with Lexical Dependency) that includes sequential and semantic structures of the grammars. With CFG describing the sequential structure of grammar, lexical dependencies between sentence elements can be designated in the definition system. Through the defined grammars, the implemented editor guides users' narratives in more familiar expressions with a domain-specific ontology and translates the content into RDF triples.