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Parsing Natural Language Sentences by Semi-supervised Methods

2015/06/16 by Rudolf Rosa, Rosa, Rudolf
Computer Science · #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling #cs.CL

paper · pdf · doi:10.48550/arxiv.1506.04897

Dissertation interim report. Overlap with papers accepted to ACL 2015 and Depling 2015, and a paper under review at IWPT 2015

arxiv created 2015/06/16 · arxiv updated 2015/06/17

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.

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