A pipeline model for bottom-up dependency parsing

Ming-Wei Chang, Quang Do, Dan Roth
2006 Proceedings of the Tenth Conference on Computational Natural Language Learning - CoNLL-X '06   unpublished
We present a new machine learning framework for multi-lingual dependency parsing. The framework uses a linear, pipeline based, bottom-up parsing algorithm, with a look ahead local search that serves to make the local predictions more robust. As shown, the performance of the first generation of this algorithm is promising.
doi:10.3115/1596276.1596311 fatcat:ozw26e3vibf4xdoxe3gdpep6vu