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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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- en |
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license: mit |
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model-index: |
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- name: en_skillner |
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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: 0.4605714286 |
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- name: NER Recall |
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type: recall |
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value: 0.4574347333 |
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- name: NER F Score |
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type: f_score |
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value: 0.4589977221 |
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--- |
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A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT from job adverts. |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `en_skillner` | |
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| **Version** | `3.7.1` | |
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| **spaCy** | `>=3.7.4,<3.8.0` | |
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| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | |
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| **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | |
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| **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) | |
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| **Sources** | [OntoNotes 5](https://catalog.ldc.upenn.edu/LDC2013T19) (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br>[ClearNLP Constituent-to-Dependency Conversion](https://github.com/clir/clearnlp-guidelines/blob/master/md/components/dependency_conversion.md) (Emory University)<br>[WordNet 3.0](https://wordnet.princeton.edu/) (Princeton University)<br>[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) | |
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| **License** | `MIT` | |
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| **Author** | [nestauk](https://explosion.ai) | |
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### Label Scheme |
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<details> |
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<summary>View label scheme (3 labels for 1 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `SKILL`, `EXPERIENCE`, `BENEFIT` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| --- | --- | |
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| `ENTS_P` | 46.06 | |
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| `ENTS_R` | 45.74 | |
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| `ENTS_F` | 45.90 | |
