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        <title>Using Bilingual Chinese-English Word Alignments to Resolve PP-attachment Ambiguity in English</title>
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        <namePart type="given">Victoria</namePart>
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    <abstract>Errors in English parse trees impact the quality of syntax-based MT systems trained using those parses. Frequent sources of error for English parsers include PP-attachment ambiguity, NP-bracketing ambiguity, and coordination ambiguity. Not all ambiguities are preserved across languages. We examine a common type of ambiguity in English that is not preserved in Chinese: given a sequence “VP NP PP”, should the PP be attached to the main verb, or to the object noun phrase? We present a discriminative method for exploiting bilingual Chinese-English word alignments to resolve this ambiguity in English. On a held-out test set of Chinese-English parallel sentences, our method achieves 86.3% accuracy on this PP-attachment disambiguation task, an improvement of 4% over the accuracy of the baseline Collins parser (82.3%).</abstract>
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%0 Conference Proceedings
%T Using Bilingual Chinese-English Word Alignments to Resolve PP-attachment Ambiguity in English
%A Fossum, Victoria
%A Knight, Kevin
%S Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Student Research Workshop
%D 2008
%8 oct 21 25
%I Association for Machine Translation in the Americas
%C Waikiki, USA
%F fossum-knight-2008-using
%X Errors in English parse trees impact the quality of syntax-based MT systems trained using those parses. Frequent sources of error for English parsers include PP-attachment ambiguity, NP-bracketing ambiguity, and coordination ambiguity. Not all ambiguities are preserved across languages. We examine a common type of ambiguity in English that is not preserved in Chinese: given a sequence “VP NP PP”, should the PP be attached to the main verb, or to the object noun phrase? We present a discriminative method for exploiting bilingual Chinese-English word alignments to resolve this ambiguity in English. On a held-out test set of Chinese-English parallel sentences, our method achieves 86.3% accuracy on this PP-attachment disambiguation task, an improvement of 4% over the accuracy of the baseline Collins parser (82.3%).
%U https://aclanthology.org/2008.amta-srw.2
%P 245-253

Markdown (Informal)

[Using Bilingual Chinese-English Word Alignments to Resolve PP-attachment Ambiguity in English](https://aclanthology.org/2008.amta-srw.2) (Fossum & Knight, AMTA 2008)

• Using Bilingual Chinese-English Word Alignments to Resolve PP-attachment Ambiguity in English (Fossum & Knight, AMTA 2008)

ACL

• Victoria Fossum and Kevin Knight. 2008. Using Bilingual Chinese-English Word Alignments to Resolve PP-attachment Ambiguity in English. In Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Student Research Workshop, pages 245–253, Waikiki, USA. Association for Machine Translation in the Americas.