Natural Language Parsing

Abstract

Automatic natural language processing captures a lion’s share of the attention in open information management. In one way or another, many applications have to deal with natural language input. In this chapter the authors investigate the problem of natural language parsing from the perspective of biolinguistics. They argue that the human mind succeeds in the parsing task without the help of languagespecific rules of parsing and language-specific rules of grammar. Instead, there is a universal parser incorporating a universal grammar. The main argument comes from language acquisition: Children cannot learn language specific parsing rules by rule induction due to the complexity of unconstrained inductive learning. They suggest that the universal parser presents a manageable solution to the problem of automatic natural language processing when compared with parsers tinkered for specific purposes. A model for a completely language independent parser is presented, taking a recent minimalist theory as a starting point.