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- name: Sentences F-Score
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type: f_score
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value: 0.9968010237
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---
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| Feature | Description |
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| --- | --- |
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- name: Sentences F-Score
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type: f_score
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value: 0.9968010237
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datasets:
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- UD-Filipino/UD_Tagalog-NewsCrawl
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pipeline_tag: token-classification
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library_name: spacy
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---
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<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/634e20a0c1ce28f1de920cc4/k7SJny1M3lDa5CH_T1bp3.png" width="130" height="130" align="right" />
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# UD Parser (Multilingual context-sensitive vectors + transition-based parser)
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This is the spaCy pipeline trained on [UD-NewsCrawl](https://huggingface.co/datasets/UD-Filipino/UD_Tagalog-NewsCrawl).
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It uses [fastText word-embeddings for Tagalog](https://huggingface.co/facebook/fasttext-tl-vectors).
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It is trained using a transition-based parser based on [Honnibal and Johnson (2015)](https://aclanthology.org/D15-1162/) and can perform dependency parsing, lemmatization, and morphological annotation.
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The trainable lemmatizer is based on [Muller et al. (2015)](https://aclanthology.org/D15-1272/).
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More information can be found [in this blog post](https://explosion.ai/blog/edit-tree-lemmatizer).
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| Feature | Description |
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| --- | --- |
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