File size: 1,695 Bytes
24187ff 855789c 24187ff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | ---
tags:
- spacy
- token-classification
language:
- nl
model-index:
- name: nl_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.5
- name: NER Recall
type: recall
value: 0.4
- name: NER F Score
type: f_score
value: 0.4444444444
---
| Feature | Description |
| --- | --- |
| **Name** | `nl_ner` |
| **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]() |
### 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.
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 0.1
46 documenten (https://github.com/RaThorat/my-chatbot-project/tree/main/Data/txt) uit de DUS-i website gedownload, schoongemaakt, samengesteld in combined_documents.txt
### Label Scheme
<details>
<summary>View label scheme (7 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `BEDRAG`, `LOC`, `ORG`, `PERSOON`, `PROJECT`, `SUB`, `TIJD` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 44.44 |
| `ENTS_P` | 50.00 |
| `ENTS_R` | 40.00 |
| `TOK2VEC_LOSS` | 6462.80 |
| `NER_LOSS` | 14799.70 | |