Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- id
license:
- other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: nergrit-corpus
pretty_name: Nergrit Corpus
dataset_info:
- config_name: ner
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': B-CRD
'1': B-DAT
'2': B-EVT
'3': B-FAC
'4': B-GPE
'5': B-LAN
'6': B-LAW
'7': B-LOC
'8': B-MON
'9': B-NOR
'10': B-ORD
'11': B-ORG
'12': B-PER
'13': B-PRC
'14': B-PRD
'15': B-QTY
'16': B-REG
'17': B-TIM
'18': B-WOA
'19': I-CRD
'20': I-DAT
'21': I-EVT
'22': I-FAC
'23': I-GPE
'24': I-LAN
'25': I-LAW
'26': I-LOC
'27': I-MON
'28': I-NOR
'29': I-ORD
'30': I-ORG
'31': I-PER
'32': I-PRC
'33': I-PRD
'34': I-QTY
'35': I-REG
'36': I-TIM
'37': I-WOA
'38': O
splits:
- name: train
num_bytes: 5428411
num_examples: 12532
- name: test
num_bytes: 1135577
num_examples: 2399
- name: validation
num_bytes: 1086437
num_examples: 2521
download_size: 14988232
dataset_size: 7650425
- config_name: sentiment
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': B-NEG
'1': B-NET
'2': B-POS
'3': I-NEG
'4': I-NET
'5': I-POS
'6': O
splits:
- name: train
num_bytes: 3167972
num_examples: 7485
- name: test
num_bytes: 1097517
num_examples: 2317
- name: validation
num_bytes: 337679
num_examples: 782
download_size: 14988232
dataset_size: 4603168
- config_name: statement
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': B-BREL
'1': B-FREL
'2': B-STAT
'3': B-WHO
'4': I-BREL
'5': I-FREL
'6': I-STAT
'7': I-WHO
'8': O
splits:
- name: train
num_bytes: 1469081
num_examples: 2405
- name: test
num_bytes: 182553
num_examples: 335
- name: validation
num_bytes: 105119
num_examples: 176
download_size: 14988232
dataset_size: 1756753
Dataset Card for [Dataset Name]
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: PT Gria Inovasi Teknologi
- Repository: Nergrit Corpus
- Paper:
- Leaderboard:
- Point of Contact: Taufiqur Rohman
Dataset Summary
Nergrit Corpus is a dataset collection of Indonesian Named Entity Recognition, Statement Extraction, and Sentiment Analysis developed by PT Gria Inovasi Teknologi (GRIT).
Supported Tasks and Leaderboards
[More Information Needed]
Languages
Indonesian
Dataset Structure
A data point consists of sentences seperated by empty line and tab-seperated tokens and tags.
{'id': '0',
'tokens': ['Gubernur', 'Bank', 'Indonesia', 'menggelar', 'konferensi', 'pers'],
'ner_tags': [9, 28, 28, 38, 38, 38],
}
Data Instances
[More Information Needed]
Data Fields
id: id of the sampletokens: the tokens of the example textner_tags: the NER tags of each token
Named Entity Recognition
The ner_tags correspond to this list:
"B-CRD", "B-DAT", "B-EVT", "B-FAC", "B-GPE", "B-LAN", "B-LAW", "B-LOC", "B-MON", "B-NOR",
"B-ORD", "B-ORG", "B-PER", "B-PRC", "B-PRD", "B-QTY", "B-REG", "B-TIM", "B-WOA",
"I-CRD", "I-DAT", "I-EVT", "I-FAC", "I-GPE", "I-LAN", "I-LAW", "I-LOC", "I-MON", "I-NOR",
"I-ORD", "I-ORG", "I-PER", "I-PRC", "I-PRD", "I-QTY", "I-REG", "I-TIM", "I-WOA", "O",
The ner_tags have the same format as in the CoNLL shared task: a B denotes the first item of a phrase and an I any non-initial word. The dataset contains 19 following entities
'CRD': Cardinal
'DAT': Date
'EVT': Event
'FAC': Facility
'GPE': Geopolitical Entity
'LAW': Law Entity (such as Undang-Undang)
'LOC': Location
'MON': Money
'NOR': Political Organization
'ORD': Ordinal
'ORG': Organization
'PER': Person
'PRC': Percent
'PRD': Product
'QTY': Quantity
'REG': Religion
'TIM': Time
'WOA': Work of Art
'LAN': Language
Sentiment Analysis
The ner_tags correspond to this list:
"B-NEG", "B-NET", "B-POS",
"I-NEG", "I-NET", "I-POS",
"O",
Statement Extraction
The ner_tags correspond to this list:
"B-BREL", "B-FREL", "B-STAT", "B-WHO",
"I-BREL", "I-FREL", "I-STAT", "I-WHO",
"O"
The ner_tags have the same format as in the CoNLL shared task: a B denotes the first item of a phrase and an I any non-initial word.
Data Splits
The dataset is splitted in to train, validation and test sets.
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
The annotators are listed in the Nergrit Corpus repository
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
[More Information Needed]
Contributions
Thanks to @cahya-wirawan for adding this dataset.