Statistical Dependency Parsing
Statistical Dependency Parsing is a computational method within dependency grammar that identifies syntactic dependencies between words in a sentence using probabilistic models trained on annotated corpora to predict the most likely dependency structure.
108
Publications
8.2K
Citations
259
Authors
98
Institutions
Publications per year
2017–2026
5
Parents
108
Three generative, lexicalised models for statistical parsing
Michael Collins · 1997 · 750 citations
A new statistical parser based on bigram lexical dependencies
Michael Collins · 1996 · 622 citations · Full text
Japanese dependency analysis using cascaded chunking
Taku Kudo, Yūji Matsumoto · 2002 · 480 citations
1–5 of 108
259
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University of Illinois Urbana-Champaign, United States
4 publications · 707 citations
4
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1–5 of 259
98
University of Pennsylvania
Philadelphia, United States
9 h-index
13 publications
2K citations
Carnegie Mellon University
Pittsburgh, United States
8 h-index
22 publications
1.5K citations

University of Edinburgh
Edinburgh, United Kingdom
7 h-index
13 publications
1.7K citations

Uppsala University
Uppsala, Sweden
6 h-index
8 publications
327 citations
Charles University
Prague, Czechia
5 h-index
10 publications
580 citations
Google (United States)
Mountain View, United States
4 h-index
12 publications
1.1K citations

Johns Hopkins University
Baltimore, United States
3 h-index
5 publications
273 citations

Cornell University
Ithaca, United States
3 h-index
6 publications
312 citations
1–8 of 98
4 publications · 533 citations
4
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Repository · 3 publications · 65 citations
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Repository · 2 publications · 93 citations
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Repository · 2 publications · 184 citations
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Conference · 1 publications · 58 citations
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