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- W179181610 abstract "Considering the difficulties inherent in the manual construction of natural language parsers, we have designed and implemented our system Gcrind which is capable of learning a sequence of context-dependent parsing actions from an arbitrary corpus containing labelled parse trees. To achieve this, Grind combines two established methods of machine learning: transformation-based learning (TBL) and inductive logic programming (ILP). Being trained and tested on corpus SUSANNE, Grind reaches the accuracy of 96 % and the recall of 68%." @default.
- W179181610 created "2016-06-24" @default.
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- W179181610 date "2001-01-01" @default.
- W179181610 modified "2023-09-27" @default.
- W179181610 title "Learning to Parse from a Treebank: Combining TBL and ILP" @default.
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- W179181610 doi "https://doi.org/10.1007/3-540-44797-0_15" @default.
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