Datasets:
pretty_name: NoReC
annotations_creators:
- expert-generated
language_creators:
- found
language:
- nb
- nn
- 'no'
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: norec
dataset_info:
features:
- name: idx
dtype: string
- name: text
dtype: string
- name: tokens
sequence: string
- name: lemmas
sequence: string
- name: pos_tags
sequence:
class_label:
names:
'0': ADJ
'1': ADP
'2': ADV
'3': AUX
'4': CCONJ
'5': DET
'6': INTJ
'7': NOUN
'8': NUM
'9': PART
'10': PRON
'11': PROPN
'12': PUNCT
'13': SCONJ
'14': SYM
'15': VERB
'16': X
- name: xpos_tags
sequence: string
- name: feats
sequence: string
- name: head
sequence: string
- name: deprel
sequence: string
- name: deps
sequence: string
- name: misc
sequence: string
splits:
- name: train
num_bytes: 1254757266
num_examples: 680792
- name: validation
num_bytes: 189534106
num_examples: 101106
- name: test
num_bytes: 193801708
num_examples: 101594
download_size: 212492611
dataset_size: 1638093080
Dataset Card for NoReC
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Repository: https://github.com/ltgoslo/norec
- Paper: http://www.lrec-conf.org/proceedings/lrec2018/pdf/851.pdf
- Leaderboard: [More Information Needed]
- Point of Contact: [More Information Needed]
Dataset Summary
This dataset contains Norwegian Review Corpus (NoReC), created for the purpose of training and evaluating models for document-level sentiment analysis. More than 43,000 full-text reviews have been collected from major Norwegian news sources and cover a range of different domains, including literature, movies, video games, restaurants, music and theater, in addition to product reviews across a range of categories. Each review is labeled with a manually assigned score of 1–6, as provided by the rating of the original author.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The sentences in the dataset are in Norwegian (nb, nn, no).
Dataset Structure
Data Instances
A sample from training set is provided below:
{'deprel': ['det',
'amod',
'cc',
'conj',
'nsubj',
'case',
'nmod',
'cop',
'case',
'case',
'root',
'flat:name',
'flat:name',
'punct'],
'deps': ['None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None'],
'feats': ["{'Gender': 'Masc', 'Number': 'Sing', 'PronType': 'Dem'}",
"{'Definite': 'Def', 'Degree': 'Pos', 'Number': 'Sing'}",
'None',
"{'Definite': 'Def', 'Degree': 'Pos', 'Number': 'Sing'}",
"{'Definite': 'Def', 'Gender': 'Masc', 'Number': 'Sing'}",
'None',
'None',
"{'Mood': 'Ind', 'Tense': 'Pres', 'VerbForm': 'Fin'}",
'None',
'None',
'None',
'None',
'None',
'None'],
'head': ['5',
'5',
'4',
'2',
'11',
'7',
'5',
'11',
'11',
'11',
'0',
'11',
'11',
'11'],
'idx': '000000-02-01',
'lemmas': ['den',
'andre',
'og',
'sist',
'sesong',
'av',
'Rome',
'være',
'ute',
'på',
'DVD',
'i',
'Norge',
'$.'],
'misc': ['None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
"{'SpaceAfter': 'No'}",
'None'],
'pos_tags': [5, 0, 4, 0, 7, 1, 11, 3, 1, 1, 11, 1, 11, 12],
'text': 'Den andre og siste sesongen av Rome er ute på DVD i Norge.',
'tokens': ['Den',
'andre',
'og',
'siste',
'sesongen',
'av',
'Rome',
'er',
'ute',
'på',
'DVD',
'i',
'Norge',
'.'],
'xpos_tags': ['None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None',
'None']}
Data Fields
The data instances have the following fields:
- deprel: [More Information Needed]
- deps: [More Information Needed]
- feats: [More Information Needed]
- head: [More Information Needed]
- idx: index
- lemmas: lemmas of all tokens
- misc: [More Information Needed]
- pos_tags: part of speech tags
- text: text string
- tokens: tokens
- xpos_tags: [More Information Needed]
The part of speech taggs correspond to these labels: "ADJ" (0), "ADP" (1), "ADV" (2), "AUX" (3), "CCONJ" (4), "DET" (5), "INTJ" (6), "NOUN" (7), "NUM" (8), "PART" (9), "PRON" (10), "PROPN" (11), "PUNCT" (12), "SCONJ" (13), "SYM" (14), "VERB" (15), "X" (16),
Data Splits
The training, validation, and test set contain 680792, 101106, and 101594 sentences respectively.
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
[More Information Needed]
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
[More Information Needed]
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
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
@InProceedings{VelOvrBer18,
author = {Erik Velldal and Lilja {\O}vrelid and
Eivind Alexander Bergem and Cathrine Stadsnes and
Samia Touileb and Fredrik J{\o}rgensen},
title = {{NoReC}: The {N}orwegian {R}eview {C}orpus},
booktitle = {Proceedings of the 11th edition of the
Language Resources and Evaluation Conference},
year = {2018},
address = {Miyazaki, Japan},
pages = {4186--4191}
}
Contributions
Thanks to @abhishekkrthakur for adding this dataset.