Correspondence-Guided Synchronous Parsing of Parallel Corpora
Abstract
We present an efficient dynamic programming algorithm for synchronous parsing of sentence pairs from a parallel corpus with a given word alignment. Unless there is a large proportion of words without a correspondence in the other language, the worstcase complexity is significantly reduced over standard synchronous parsing. The theoretical complexity results are corroborated by a quantitative experimental evaluation. Our longer-term goal is to induce monolingual grammars from a parallel corpus, exploiting implicit information about syntactic structure obtained from correspondence patterns. 1 Here we provide an important prerequisite for parallel corpusbased grammar induction: an efficient algorithm for synchronous
Cite
Text
Kuhn. "Correspondence-Guided Synchronous Parsing of Parallel Corpora." International Joint Conference on Artificial Intelligence, 2005.Markdown
[Kuhn. "Correspondence-Guided Synchronous Parsing of Parallel Corpora." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/kuhn2005ijcai-correspondence/)BibTeX
@inproceedings{kuhn2005ijcai-correspondence,
title = {{Correspondence-Guided Synchronous Parsing of Parallel Corpora}},
author = {Kuhn, Jonas},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2005},
pages = {1694-1695},
url = {https://mlanthology.org/ijcai/2005/kuhn2005ijcai-correspondence/}
}