Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
A systematic comparison of various statistical alignment models
Computational Linguistics
A cascaded finite-state parser for German
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Inducing multilingual POS taggers and NP bracketers via robust projection across aligned corpora
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Bootstrapping parsers via syntactic projection across parallel texts
Natural Language Engineering
Efficient parsing of highly ambiguous context-free grammars with bit vectors
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Rich bitext projection features for parse reranking
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Two languages are better than one (for syntactic parsing)
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Bilingually-constrained (monolingual) shift-reduce parsing
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Cross-lingual annotation projection of semantic roles
Journal of Artificial Intelligence Research
Using large monolingual and bilingual corpora to improve coordination disambiguation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
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We present a method for disambiguating syntactic subjects from syntactic objects (a frequent ambiguity) in German sentences taken from an English-German bitext. We exploit the fact that subject and object are usually easily determined in English. We show that a simple method disambiguates some subject-object ambiguities in German, while making few errors. We view this procedure as the first step in automatically acquiring (mostly) correct labeled data. We also evaluate using it to improve a state of the art statistical parser.