Experiments with an ensemble of Spanish dependency parsers
This article presents an ensemble system for dependency parsing of Spanish that combines three machine-learning-based dependency parsers. The system operates in two stages. In the ﬁrst stage, each of the three parsers analyzes an input sentence and produces a dependency graph. In the second stage, a voting system distills a ﬁnal dependency graph out of the three ﬁrst-stage dependency graphs.