Paper: Inspecting the Structural Biases of Dependency Parsing Algorithms

ACL ID W10-2927
Title Inspecting the Structural Biases of Dependency Parsing Algorithms
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2010
Authors

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 un- covering some of the structural bias inher- ent 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 spe- cific differences and commonalities be- tween the parsing systems, and improves our understandi...