The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Natural Language Parsing: New Perspectives from Contemporary Biolinguistics
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.
Related Content
Christine Kosmopoulos.
© 2022.
22 pages.
|
Melkamu Beyene, Solomon Mekonnen Tekle, Daniel Gelaw Alemneh.
© 2022.
21 pages.
|
Rajkumari Sofia Devi, Ch. Ibohal Singh.
© 2022.
21 pages.
|
Ida Fajar Priyanto.
© 2022.
16 pages.
|
Murtala Ismail Adakawa.
© 2022.
27 pages.
|
Shimelis Getu Assefa.
© 2022.
17 pages.
|
Angela Y. Ford, Daniel Gelaw Alemneh.
© 2022.
22 pages.
|
|
|