File size: 2,981 Bytes
47e8e78 c1841f7 b68bf94 09388ce c1841f7 47e8e78 02d1b4a 29c51f7 02d1b4a |
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 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 |
---
annotations_creators:
- expert-generated
- machine-generated
language_creators:
- found
language:
- da
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- dane
- extended|other-Danish-Universal-Dependencies-treebank
- DANSK
task_categories:
- token-classification
task_ids:
- named-entity-recognition
- part-of-speech
paperswithcode_id: dane
pretty_name: DaNE+
dataset_info:
features:
- name: text
dtype: string
- name: ents
list:
- name: end
dtype: int64
- name: label
dtype: string
- name: start
dtype: int64
- name: sents
list:
- name: end
dtype: int64
- name: start
dtype: int64
- name: tokens
list:
- name: dep
dtype: string
- name: end
dtype: int64
- name: head
dtype: int64
- name: id
dtype: int64
- name: lemma
dtype: string
- name: morph
dtype: string
- name: pos
dtype: string
- name: start
dtype: int64
- name: tag
dtype: string
splits:
- name: train
num_bytes: 7886693
num_examples: 4383
- name: dev
num_bytes: 1016350
num_examples: 564
- name: test
num_bytes: 991137
num_examples: 565
download_size: 1627548
dataset_size: 9894180
---
# DaNE+
This is a version of [DaNE](https://huggingface.co/datasets/dane), where the original NER labels have been updated to follow the ontonotes annotation scheme. The annotation process used the model trained on the Danish dataset [DANSK](https://huggingface.co/datasets/chcaa/DANSK) for the first round of annotation and then all the discrepancies were manually reviewed and corrected by Kenneth C. Enevoldsen. A discrepancy include notably also includes newly added entities such as `PRODUCT` and `WORK_OF_ART`. Thus in practice a great deal of entities were manually reviews. If there was an uncertainty the annotation was left as it was.
The additional annotations (e.g. part-of-speech tags) stems from the Danish Dependency Treebank, however, if you wish to use these I would recommend using the latest version as this version here will likely become outdated over time.
## Process of annotation
1) Install the requirements:
```
--extra-index-url pip install prodigy -f https://{DOWNLOAD KEY}@download.prodi.gy
prodigy>=1.11.0,<2.0.0
```
2) Create outline dataset
```bash
python annotate.py
```
3) Review and correction annotation using prodigy:
Add datasets to prodigy
```bash
prodigy db-in dane reference.jsonl
prodigy db-in dane_plus_mdl_pred predictions.jsonl
```
Run review using prodigy:
```bash
prodigy review daneplus dane_plus_mdl_pred,dane --view-id ner_manual --l NORP,CARDINAL,PRODUCT,ORGANIZATION,PERSON,WORK_OF_ART,EVENT,LAW,QUANTITY,DATE,TIME,ORDINAL,LOCATION,GPE,MONEY,PERCENT,FACILITY
```
Export the dataset:
```bash
prodigy data-to-spacy daneplus --ner daneplus --lang da -es 0
```
4) Redo the original split:
```bash
python split.py
```
|