Supertagging : Using Complex Lexical Descriptions in Natural Language Processing (Hardcover)

Customer Reviews   Write a Review

Be the first to review this item and earn 25 Rakuten Super Points™

Product Overview

The last decade has seen computational implementations of large hand-crafted natural language grammars in formal frameworks such as Tree-Adjoining Grammar (TAG), Combinatory Categorical Grammar (CCG), Head-driven Phrase Structure Grammar (HPSG), and Lexical Functional Grammar (LFG). Grammars in these frameworks typically associate linguistically motivated rich descriptions (Supertags) with words. With the availability of parse-annotated corpora, grammars in the TAG and CCG frameworks have also been automatically extracted while maintaining the linguistic relevance of the extracted Supertags. In these frameworks, Supertags are designed so that complex linguistic constraints are localized to operate within the domain of those descriptions. While this localization increases local ambiguity, the process of disambiguation (Supertagging) provides a unique way of combining linguistic and statistical information. This volume investigates the theme of employing statistical approaches with linguistically motivated representations and its impact on Natural Language Processing tasks. In particular, the contributors describe research in which words are associated with Supertags that are the primitives of different grammar formalisms including Lexicalized Tree-Adjoining Grammar (LTAG). ContributorsJens B?cker, Srinivas Bangalore, Akshar Bharati, Pierre Boullier, Tomas By, John Chen, Stephen Clark, Berthold Crysmann, James R. Curran, Kilian Foth, Robert Frank, Karin Harbusch, Sa?a Hasan, Aravind Joshi,Vincenzo Lombardo, Takuya Matsuzaki, Alessandro Mazzei, Wolfgang Menzel, Yusuke Miyao, Richard Moot, Alexis Nasr, G?nter Neumann, Martha Palmer, Owen Rambow, Rajeev Sangal, Anoop Sarkar, Giorgio Satta, Libin Shen, Patrick Sturt, Jun'ichi Tsujii, K. Vijay-Shanker, Wen Wang, Fei Xia

Specifications

Publisher Bradford Books
Mfg Part# 9780262013871
SKU 212646578
Format Hardcover
ISBN10 0262013878
Release Date 3/1/2010
Product Attributes
Book Format Hardcover
Minimum Age 22
Number of Pages 0488
Publisher MIT Press (MA)
loading
Sold Out
Sorry, you missed the deal!
This product is currently not available.
ADVERTISEMENT
Promotions & Offers (1)
  •  custom promo
    5% Back* Sitewide with Promo Code Rewardme *See page for details
ADVERTISEMENT
ADVERTISEMENT