Parsing Natural Language Sentences by Semi-supervised Methods
Computation and Language
2015-06-17 v1
Abstract
We present our work on semi-supervised parsing of natural language sentences, focusing on multi-source crosslingual transfer of delexicalized dependency parsers. We first evaluate the influence of treebank annotation styles on parsing performance, focusing on adposition attachment style. Then, we present KLcpos3, an empirical language similarity measure, designed and tuned for source parser weighting in multi-source delexicalized parser transfer. And finally, we introduce a novel resource combination method, based on interpolation of trained parser models.
Cite
@article{arxiv.1506.04897,
title = {Parsing Natural Language Sentences by Semi-supervised Methods},
author = {Rudolf Rosa},
journal= {arXiv preprint arXiv:1506.04897},
year = {2015}
}
Comments
Dissertation interim report. Overlap with papers accepted to ACL 2015 and Depling 2015, and a paper under review at IWPT 2015