OldSlavNet: A scalable Early Slavic dependency parser trained on modern language data

SOFTWARE IMPACTS(2021)

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摘要
Historical languages are increasingly being modelled computationally. Syntactically annotated texts are often a sine-qua-non in their modelling, but parsing of pre-modern language varieties faces great data sparsity, intensified by high levels of orthographic variation. In this paper we present a good-quality Early Slavic dependency parser, attained via manipulation of modern Slavic data to resemble the orthography and morphosyntax of pre-modern varieties. The tool can be deployed to expand historical treebanks, which are crucial for data collection and quantification, and beneficial to downstream NLP tasks and historical text mining.
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关键词
Neural networks, Dependency parsing, Cross-lingual transfer, Treebanks, Early Slavic
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