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Note on code to generate dataset
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---
license: other
license_name: other
license_link: LICENSE
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: pos_tags
sequence:
class_label:
names:
'0': '"'
'1': ''''''
'2': '#'
'3': $
'4': (
'5': )
'6': ','
'7': .
'8': ':'
'9': '``'
'10': CC
'11': CD
'12': DT
'13': EX
'14': FW
'15': IN
'16': JJ
'17': JJR
'18': JJS
'19': LS
'20': MD
'21': NN
'22': NNP
'23': NNPS
'24': NNS
'25': NN|SYM
'26': PDT
'27': POS
'28': PRP
'29': PRP$
'30': RB
'31': RBR
'32': RBS
'33': RP
'34': SYM
'35': TO
'36': UH
'37': VB
'38': VBD
'39': VBG
'40': VBN
'41': VBP
'42': VBZ
'43': WDT
'44': WP
'45': WP$
'46': WRB
- name: chunk_tags
sequence:
class_label:
names:
'0': O
'1': B-ADJP
'2': I-ADJP
'3': B-ADVP
'4': I-ADVP
'5': B-CONJP
'6': I-CONJP
'7': B-INTJ
'8': I-INTJ
'9': B-LST
'10': I-LST
'11': B-NP
'12': I-NP
'13': B-PP
'14': I-PP
'15': B-PRT
'16': I-PRT
'17': B-SBAR
'18': I-SBAR
'19': B-UCP
'20': I-UCP
'21': B-VP
'22': I-VP
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-PER
'2': I-PER
'3': B-ORG
'4': I-ORG
'5': B-LOC
'6': I-LOC
'7': B-MISC
'8': I-MISC
- name: ner_labels
sequence: string
- name: sentence
dtype: string
- name: entities
struct:
- name: LOC
sequence: string
- name: MISC
sequence: string
- name: ORG
sequence: string
- name: PER
sequence: string
splits:
- name: train
num_bytes: 9823344
num_examples: 14041
- name: validation
num_bytes: 2461842
num_examples: 3250
- name: test
num_bytes: 2248983
num_examples: 3453
download_size: 3369931
dataset_size: 14534169
task_categories:
- text-generation
- token-classification
language:
- en
size_categories:
- 10K<n<100K
---
# Dataset Card for CoNLL-2003 with NER Workflow Enhancements
This dataset is a modified version of the CoNLL-2003 dataset, enhanced to support an LLM-based Named Entity Recognition (NER) workflow. Two new columns, `sentence` and `entities`, have been added. You can find the code used to generate this version together with the data files.
## Named Entities
As in the original CoNLL-2003 task, this dataset focuses on four types of named entities:
- Persons (PER)
- Locations (LOC)
- Organizations (ORG)
- Miscellaneous entities (MISC) that do not belong to the previous three groups.
## Workflow
The LLM is provided with the `sentence` and a prompt containing NER task instructions. It is then asked to output a dictionary with the identified Named Entities.
### Example
For the sentence:
```
EU rejects German call to boycott British lamb.
```
The expected output is:
```json
{
"entities": {
"LOC": [],
"MISC": ["German", "British"],
"ORG": ["EU"],
"PER": []
}
}
```
## Original Dataset
You can find the original dataset and its associated documentation at the [CoNLL-2003 dataset on Hugging Face](https://huggingface.co/datasets/eriktks/conll2003).