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--- |
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tags: |
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- spacy |
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- token-classification |
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language: |
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- mk |
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license: cc-by-sa-4.0 |
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model-index: |
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- name: mk_core_news_md |
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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: 0.7543402778 |
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- name: NER Recall |
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type: recall |
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value: 0.7395744681 |
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- name: NER F Score |
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type: f_score |
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value: 0.7468844005 |
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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: 0.9309414621 |
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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: 0.6916256158 |
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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: 0.5300492611 |
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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: 0.7123287671 |
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--- |
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### Details: https://spacy.io/models/mk#mk_core_news_md |
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Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `mk_core_news_md` | |
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| **Version** | `3.3.0` | |
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| **spaCy** | `>=3.3.0.dev0,<3.4.0` | |
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| **Default Pipeline** | `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | |
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| **Components** | `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | |
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| **Vectors** | 274587 keys, 20000 unique vectors (300 dimensions) | |
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| **Sources** | [Macedonian Corpus](https://blog.netcetera.com/macedonian-spacy-f3c85484777f) (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska)<br />[Macedonian Corpus](https://blog.netcetera.com/macedonian-spacy-f3c85484777f) (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska)<br />[Macedonian Corpus](https://blog.netcetera.com/macedonian-spacy-f3c85484777f) (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | |
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| **License** | `CC BY-SA 4.0` | |
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| **Author** | [Explosion](https://explosion.ai) | |
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### Label Scheme |
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<details> |
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<summary>View label scheme (53 labels for 3 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`morphologizer`** | `POS=PROPN`, `POS=AUX`, `POS=ADJ`, `POS=NOUN`, `POS=ADP`, `POS=PUNCT`, `POS=CONJ`, `POS=NUM`, `POS=VERB`, `POS=PRON`, `POS=ADV`, `POS=SCONJ`, `POS=PART`, `POS=SYM`, `POS=X`, `_`, `POS=INTJ` | |
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| **`parser`** | `ROOT`, `advmod`, `att`, `aux`, `cc`, `dep`, `det`, `dobj`, `iobj`, `neg`, `nsubj`, `pobj`, `poss`, `pozm`, `pozv`, `prep`, `punct`, `relcl` | |
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| --- | --- | |
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| `TOKEN_ACC` | 100.00 | |
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| `TOKEN_P` | 100.00 | |
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| `TOKEN_R` | 100.00 | |
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| `TOKEN_F` | 100.00 | |
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| `SENTS_P` | 75.36 | |
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| `SENTS_R` | 67.53 | |
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| `SENTS_F` | 71.23 | |
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| `DEP_UAS` | 69.16 | |
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| `DEP_LAS` | 53.00 | |
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| `ENTS_P` | 75.43 | |
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| `ENTS_R` | 73.96 | |
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| `ENTS_F` | 74.69 | |
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| `POS_ACC` | 93.09 | |
