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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_legal_ner_trf |
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results: [] |
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--- |
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Indian Legal Named Entity Recognition: Identifying relevant entities in an Indian legal document |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `en_legal_ner_trf` | |
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| **Version** | `3.2.0` | |
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| **spaCy** | `>=3.2.2,<3.3.0` | |
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| **Default Pipeline** | `transformer`, `ner` | |
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| **Components** | `transformer`, `ner` | |
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | |
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| **Sources** | [Indian Legal NER Training data](https://storage.googleapis.com/indianlegalbert/OPEN_SOURCED_FILES/NER/NER_TRAIN.zip) [GitHub](https://github.com/Legal-NLP-EkStep/legal_NER)| |
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| **License** | `MIT` | |
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| **Author** | [Aman Tiwari](https://www.linkedin.com/in/amant555/) | |
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### Label Scheme |
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<details> |
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<summary>View label scheme (14 labels for 1 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `CASE_NUMBER`, `COURT`, `DATE`, `GPE`, `JUDGE`, `LAWYER`, `ORG`, `OTHER_PERSON`, `PETITIONER`, `PRECEDENT`, `PROVISION`, `RESPONDENT`, `STATUTE`, `WITNESS` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| --- | --- | |
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| `Precision` | 91.474 | |
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| `Recall` | 89.956 | |
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| **`F1-Score`** | **90.709** | |
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