Ma, Yanjun and Stroppa, Nicolas and Way, Andy (2007) Alignment-guided chunking. In: TMI-07 - Proceedings of The 11th Conference on Theoretical and Methodological Issues in Machine Translation, 7-9 September 2007, Skövde, Sweden.
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We introduce an adaptable monolingual chunking approach–Alignment-Guided Chunking (AGC)–which makes use of knowledge of word alignments acquired from bilingual
corpora. Our approach is motivated by the observation that a sentence should be chunked differently depending
the foreseen end-tasks. For example, given the different
requirements of translation into (say) French and German, it is inappropriate to chunk up an English string in exactly the same way as preparation for translation into one
or other of these languages. We test our chunking approach
on two language pairs: French–English and German–English, where these two bilingual corpora share the same English sentences. Two chunkers trained on French–English
(FE-Chunker) and German–English(DE-Chunker ) respectively are used to perform chunking on the same English sentences. We construct two test sets, each suitable for French–
English and German–English respectively. The performance of the two chunkers is evaluated on the appropriate test set and with one reference translation only, we report Fscores
of 32.63% for the FE-Chunker and 40.41% for the DE-Chunker.
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