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A Neural Model For Part-of-Speech Tagging In Historical Texts.pdf

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Preview of A Neural Model for Part-of-Speech Tagging in Historical Texts
🔗 Source: aclweb.org
📊 Size: 150 KB
👤 Author: Christian Hardmeier
⬇️ Downloads: 86

Summary

A neural network model is proposed for part-of-speech (POS) tagging in historical texts, which can process historical data directly without requiring a separate spelling normalisation stage. The model uses a character-level neural network and is trained on a modern POS-tagged corpus and a historical corpus with original and normalised spellings. The model's performance is evaluated on a Swedish verb identification and a German POS tagging task, and its output is analysed to identify remaining challenges. The results show that the model's performance is similar to that of a two-stage model, and its flexibility could be exploited to address diachronic divergences in morphology and syntax in early modern Swedish with the help of data from closely related languages.

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Description

A neural network model is proposed for part-of-speech (POS) tagging in historical texts, which can process historical data directly without requiring a...

Technical Information

  • File Format: PDF
  • File Size: 150 KB
  • Pages: 10
  • Language: EN
  • Author: Christian Hardmeier
  • Total Downloads: 86
  • Last Updated: 6 days ago

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