--- tags: - spacy - token-classification language: - nl model-index: - name: nl_pipeline results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.6350364964 - name: NER Recall type: recall value: 0.5878378378 - name: NER F Score type: f_score value: 0.6105263158 --- | Feature | Description | | --- | --- | | **Name** | `nl_pipeline` | | **Version** | `0.0.0` | | **spaCy** | `>=3.6.1,<3.7.0` | | **Default Pipeline** | `tok2vec`, `ner` | | **Components** | `tok2vec`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | n/a | | **License** | n/a | | **Author** | [n/a]() | ### Label Scheme
View label scheme (7 labels for 1 components) | Component | Labels | | --- | --- | | **`ner`** | `BEDRAG`, `LOC`, `ORG`, `PERSOON`, `PROJECT`, `SUB`, `TIJD` |
### Accuracy | Type | Score | | --- | --- | | `ENTS_F` | 61.05 | | `ENTS_P` | 63.50 | | `ENTS_R` | 58.78 | | `TOK2VEC_LOSS` | 41795.01 | | `NER_LOSS` | 26551.93 | ### Description Voor meer info: https://github.com/RaThorat/my-chatbot-project Prodigy (ner.manual) is gebruikt om te annoteren van entiteiten zoals: PERSOON, ORGANISATIE, PROJECT, BEDRAG, LOCATIE, TIJDSPERIODE, SUBSIDIE, PRODUCT. prodigy ner.manual ner_dataset nl_core_news_lg ./Data/combined_documents.txt --label PERSOON,ORG,PROJECT,BEDRAG,LOC,TIJD,SUB prodigy train ./models --ner ner_dataset --lang nl --label-stats --verbose --eval-split 0.2 30 documenten (https://github.com/RaThorat/my-chatbot-project/tree/main/Data/txt) uit de DUS-i website gedownload, schoongemaakt, samengesteld in combined_documents.txt