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- W67664185 abstract "We propose the notion of a structural bias inherent in a parsing system with respect to the language it is aiming to parse. This structural bias characterizes the behaviour of a parsing system in terms of structures it tends to under- and over- produce. We propose a Boosting-based method for uncovering some of the structural bias inherent in parsing systems. We then apply our method to four English dependency parsers (an Arc-Eager and Arc-Standard transition-based parsers, and first- and second-order graph-based parsers). We show that all four parsers are biased with respect to the kind of annotation they are trained to parse. We present a detailed analysis of the biases that highlights specific differences and commonalities between the parsing systems, and improves our understanding of their strengths and weaknesses." @default.
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- W67664185 date "2010-07-15" @default.
- W67664185 modified "2023-09-26" @default.
- W67664185 title "Inspecting the Structural Biases of Dependency Parsing Algorithms" @default.
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