README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
language:
  - pl
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - text-retrieval
task_ids:
  - entity-linking-retrieval
paperswithcode_id: null
pretty_name: bprec

Dataset Card for [Dataset Name]

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

• Homepage: bprec homepage
• Repository: bprec repository
• Paper: bprec paper
• Leaderboard:
• Point of Contact:

Dataset Summary

Brand-Product Relation Extraction Corpora in Polish

Supported Tasks and Leaderboards

NER, Entity linking

Languages

Polish

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

• id: int identifier of a text
• text: string text, for example a consumer comment on the social media
• ner: extracted entities and their relationship
  • source and target: a pair of entities identified in the text
    • from: int value representing starting character of the entity
    • text: string value with the entity text
    • to: int value representing end character of the entity
    • type: one of pre-identified entity types:
      • PRODUCT_NAME
      • PRODUCT_NAME_IMP
      • PRODUCT_NO_BRAND
      • BRAND_NAME
      • BRAND_NAME_IMP
      • VERSION
      • PRODUCT_ADJ
      • BRAND_ADJ
      • LOCATION
      • LOCATION_IMP

Data Splits

No train/validation/test split provided. Current dataset configurations point to 4 domain categories for the texts:

• tele
• electro
• cosmetics
• banking

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?

[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{inproceedings,
author = {Janz, Arkadiusz and Kopociński, Łukasz and Piasecki, Maciej and Pluwak, Agnieszka},
year = {2020},
month = {05},
pages = {},
title = {Brand-Product Relation Extraction Using Heterogeneous Vector Space Representations}
}

Contributions

Thanks to @kldarek for adding this dataset.