---
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