Paper: Target Language Adaptation of Discriminative Transfer Parsers

ACL ID N13-1126
Title Target Language Adaptation of Discriminative Transfer Parsers
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

We study multi-source transfer parsing for resource-poor target languages; specifically methods for target language adaptation of delexicalized discriminative graph-based de- pendency parsers. We first show how recent insights on selective parameter sharing, based on typological and language-family features, can be applied to a discriminative parser by carefully decomposing its model features. We then show how the parser can be relexicalized and adapted using unlabeled target language data and a learning method that can incorporate diverse knowledge sources through ambiguous labelings. In the latter scenario, we exploit two sources of knowledge: arc marginals de- rived from the base parser in a self-training algorithm, and arc predictions from multiple transfer parsers in an ensemble-train...