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» Feature Forest Models for Probabilistic HPSG Parsing
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IJCNLP
2005
Springer
13 years 10 months ago
Adapting a Probabilistic Disambiguation Model of an HPSG Parser to a New Domain
Abstract. This paper describes a method of adapting a domain-independent HPSG parser to a biomedical domain. Without modifying the grammar and the probabilistic model of the origin...
Tadayoshi Hara, Yusuke Miyao, Jun-ichi Tsujii
EMNLP
2006
13 years 6 months ago
Extremely Lexicalized Models for Accurate and Fast HPSG Parsing
This paper describes an extremely lexicalized probabilistic model for fast and accurate HPSG parsing. In this model, the probabilities of parse trees are defined with only the pro...
Takashi Ninomiya, Takuya Matsuzaki, Yoshimasa Tsur...
LREC
2010
164views Education» more  LREC 2010»
13 years 6 months ago
Semantic Feature Engineering for Enhancing Disambiguation Performance in Deep Linguistic Processing
The task of parse disambiguation has gained in importance over the last decade as the complexity of grammars used in deep linguistic processing has been increasing. In this paper ...
Danielle Ben-Gera, Yi Zhang 0003, Valia Kordoni
ACL
2009
13 years 2 months ago
Improving Tree-to-Tree Translation with Packed Forests
Current tree-to-tree models suffer from parsing errors as they usually use only 1best parses for rule extraction and decoding. We instead propose a forest-based tree-to-tree model...
Yang Liu, Yajuan Lü, Qun Liu