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Update README.md
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README.md
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---
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license: cc-by-nc-sa-3.0
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---
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---
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license: cc-by-nc-sa-3.0
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language:
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- bg
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metrics:
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- accuracy
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library_name: spacy
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pipeline_tag: token-classification
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model-index:
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- name: bg_news_lg
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results:
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- task:
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name: NER
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type: token-classification
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metrics:
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- name: NER Precision
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type: precision
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value: 0.9090909091
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- name: NER Recall
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type: recall
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value: 0.8773461371
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- name: NER F Score
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type: f_score
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value: 0.8929364727
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- task:
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name: TAG
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type: token-classification
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metrics:
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- name: TAG (XPOS) Accuracy
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type: accuracy
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value: 0.9565136361
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- task:
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name: POS
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type: token-classification
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metrics:
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- name: POS (UPOS) Accuracy
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type: accuracy
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value: 0.9858305885
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- task:
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name: MORPH
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type: token-classification
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metrics:
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- name: Morph (UFeats) Accuracy
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type: accuracy
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value: 0.9645896751
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- task:
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name: LEMMA
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type: token-classification
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metrics:
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- name: Lemma Accuracy
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type: accuracy
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value: 0.9271110013
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- task:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Unlabeled Attachment Score (UAS)
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type: f_score
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value: 0.9016132533
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- task:
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name: LABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Labeled Attachment Score (LAS)
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type: f_score
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value: 0.8459063799
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- task:
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name: SENTS
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type: token-classification
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metrics:
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- name: Sentences F-Score
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type: f_score
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value: 0.939802336
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tags:
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- ner
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- named entity recognition
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- spacy
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---
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| Feature | Description |
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| --- | --- |
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| **Name** | `bg_news_trf` |
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| **Version** | `3.5.4` |
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| **spaCy** | `>=3.5.4,<3.6.0` |
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| **Default Pipeline** | `transformer`, `tagger`, `morphologizer`, `parser`, `trainable_lemmatizer`, `ner` |
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| **Components** | `transformer`, `tagger`, `morphologizer`, `parser`, `trainable_lemmatizer`, `ner` |
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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| **Sources** | [UD_Bulgarian-BTB](https://github.com/UniversalDependencies/UD_Bulgarian-BTB) (Kiril Simov and Petya Osenova) |
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| **License** | CC-BY-NC-SA-3.0 |
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| **Author** | [Ivaylo Sakelariev](https://github.com/sakelariev) |
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Bulgarian large sized pipeline for BGspaCy. Components: tok2vec, tagger, morphologizer, lemmatizer, parser, ner
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