Supertagging: Using Complex Lexical Descriptions in Natural Language Processing
作者： Srinivas Bangalore , Aravind K Joshi , None
DOI:
关键词: Natural language processing 、 Phrase structure grammar 、 Natural language 、 Categorial grammar 、 Computer science 、 Ambiguity 、 Rule-based machine translation 、 Grammar 、 Artificial intelligence 、 Linguistics 、 Lexical functional grammar 、 Head-driven phrase structure grammar
摘要: 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 (CCG), Head-driven Phrase Structure (HPSG), and Lexical Functional (LFG). Grammars these typically associate linguistically motivated rich descriptions (Supertags) with words. With the availability parse-annotated corpora, TAG CCG have also been automatically extracted while maintaining linguistic relevance Supertags. In frameworks, Supertags are designed so that complex constraints localized to operate within domain those descriptions. While this localization increases local ambiguity, process disambiguation (Supertagging) provides a unique way combining statistical information. This volume investigates theme employing approaches representations its impact on Natural Language Processing tasks. particular, contributors describe research which words associated primitives different grammar formalisms including Lexicalized (LTAG). Contributors: Jens Bcker, Srinivas Bangalore, Akshar Bharati, Pierre Boullier, Tomas By, John Chen, Stephen Clark, Berthold Crysmann, James R. Curran, Kilian Foth, Robert Frank, Karin Harbusch, Mary Harper, Saa Hasan, Aravind Joshi,Vincenzo Lombardo, Takuya Matsuzaki, Alessandro Mazzei, Wolfgang Menzel, Yusuke Miyao, Richard Moot, Alexis Nasr, Gnter Neumann, Martha Palmer, Owen Rambow, Rajeev Sangal, Anoop Sarkar, Giorgio Satta, Libin Shen, Patrick Sturt, Junichi Tsujii, K. Vijay-Shanker, Wen Wang, Fei Xia
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