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2023.eacl-main.59.pdf
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🔗 Source: aclanthology.org
📊 Size: 362 KB
📄 Pages: 16 pages
⬇️ Downloads: 64

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Researchers investigated whether pretrained contextual language models can distinguish between Hebrew homograph analyses, which is a challenging task due to the language's morphological richness and ambiguity. They evaluated existing models for contextualized Hebrew embeddings on a novel challenge set and found that contemporary models outperform non-contextualized embeddings, especially for disambiguating segmentation and morphosyntactic features. The models were more effective when the number of word-piece splits was limited and for 2-way and 3-way ambiguities. They also performed equally well for homographs with balanced and skewed distributions, and were effective with both extensive supervised training and few-shot setup.

Description

Researchers investigated whether pretrained contextual language models can distinguish between Hebrew homograph analyses, which is a challenging task due to...

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  • File Format: PDF
  • File Size: 362 KB
  • Pages: 16
  • Language: EN
  • Total Downloads: 64
  • Last Updated: 1 month ago

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