Working with a small dataset - semi-supervised dependency parsing for Irish
Teresa Lynn, Jennifer Foster, Mark Dras · 2013
We present a number of semi-supervised parsing experiments on the Irish language carried out using a small seed set of manually parsed trees and a larger, yet still relatively small, set of unlabelled sentences.We take two popular dependency parsers -one graph-based and one transition-based -and compare results for both.Results show that using semisupervised learning in the form of self-training and co-training yields only very modest improvements in parsing accuracy.We also try to use morphological information in a targeted way and fail to see any improvements.