2004 · 14 citations · 10 references
Language StudiesComputer ScienceLinguisticsComputational LinguisticsNatural Language ProcessingSyntaxGrammarLanguage ModelingNatural Language UnderstandingSyntactic AnalysisSyntax ParsingSyntax-semantics InterfaceCommonsense Natural Language InferenceContext-free GrammarsGrammar InferenceGrammar Learning From ExamplesIdentifiability ProblemLanguage SyntaxSyntax Acquisition
Context-free grammars cannot be identified in the limit from positive examples (Gold 1967), yet natural language gram-mars are more powerful than context-free grammars and hu-mans learn them with remarkable ease from positive exam-ples (Marcus 1993). Identifiability results for formal lan-guages ignore a potentially powerful source of information available to learners of natural languages, namely, meanings. This paper explores the learnability of syntax (i.e. context-free grammars) given positive examples and knowledge of lexical semantics, and the learnability of lexical semantics given knowledge of syntax. The long-term goal is to develop an approach to learning both syntax and semantics that boot-straps itself, using limited knowledge about syntax to infer additional knowledge about semantics, and limited knowl-edge about semantics to infer additional knowledge about syntax.
10
Language identification in the limit
Eric Gold · Information and Control · 1967 · 3.6K citations
Learning regular sets from queries and counterexamples
Dana Angluin · Information and Computation · 1987 · 2.1K citations
Inference of Reversible Languages
Dana Angluin · Journal of the ACM · 1982 · 534 citations · Full text
Learning words from sights and sounds: a computational model
Deb Roy · Cognitive Science · 2002 · 483 citations
J Fürlinger, Josef Hofbauer · Journal of Combinatorial Theory Series A · 1985 · 420 citations