README.md

metadata

pretty_name: NoReC
annotations_creators:
  - expert-generated
language_creators:
  - found
languages:
  - nb
  - nn
  - 'no'
licenses:
  - 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 Card Creation Guide

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

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.