Introduction to algorithms
Computing abstract decorations of parse forests using dynamic programming and algebraic power series
AMiLP '95 Proceedings of the first international AMAST workshop on Algebraic methods in language processing
Statistical Language Learning
Parsing with Context-Free Grammars and Word Statistics
Parsing with Context-Free Grammars and Word Statistics
The structure of shared forests in ambiguous parsing
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Robust German noun chunking with a probabilistic context-free grammar
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Efficient parsing for bilexical context-free grammars and head automaton grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
High precision extraction of grammatical relations
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
High precision extraction of grammatical relations
New developments in parsing technology
Efficient extraction of grammatical relations
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Dyna: extending datalog for modern AI
Datalog'10 Proceedings of the First international conference on Datalog Reloaded
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In a headed tree, each terminal word can be uniquely labeled with a governing word and grammatical relation. This labeling is a summary of a syntactic analysis which eliminates detail, reflects aspects of semantics, and for some grammatical relations (such as subject of finite verb) is nearly uncontroversial. We define a notion of expected governor markup, which sums vectors indexed by governors and scaled by probabilistic tree weights. The quantity is computed in a parse forest representation of the set of tree analyses for a given sentence, using vector sums and scaling by inside probability and flow.