1887
Volume 36, Issue 1
  • ISSN 0929-7332
  • E-ISSN: 1569-9919
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Abstract

Abstract

Massive automatic comparison of languages in parallel corpora will greatly speed up and enhance comparative syntactic research. Automatically extracting and mining syntactic differences from parallel corpora requires a pre-processing step that filters out sentence pairs that cannot be compared syntactically, for example because they involve “free” translations. In this paper we explore four possible filters: the Damerau-Levenshtein distance between POS-tags, the sentence-length ratio, the graph-edit distance between dependency parses, and a combination of the three in a logistic regression model. Results suggest that the dependency-parse filter is the most stable throughout language pairs, while the combination filter achieves the best results.

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2019-11-05
2019-11-22
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  • Article Type: Research Article
Keyword(s): dependency parses , filter , parallel corpus and syntactic comparability
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