A filter for syntactically incomparable parallel sentences
Publication date
2019-12
Editors
Berns, Janine
Tribushinina, Elena
Advisors
Supervisors
DOI
Document Type
Part of book
Metadata
Show full item recordCollections
License
taverne
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
Keywords
Taverne, Language and Linguistics, Artificial Intelligence
Citation
Kroon, M, Barbiers, S, Odijk, J & Pas, S V D 2019, A filter for syntactically incomparable parallel sentences. in J Berns & E Tribushinina (eds), Linguistics in the Netherlands 2019. AVT Publications, John Benjamins, Amsterdam, pp. 147-161.