| | --- |
| | 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 |
| | pretty_name: bprec |
| | dataset_info: |
| | - config_name: default |
| | features: |
| | - name: id |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: ner |
| | sequence: |
| | - name: source |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | - name: target |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | splits: |
| | - name: tele |
| | num_bytes: 2739015 |
| | num_examples: 2391 |
| | - name: electro |
| | num_bytes: 125999 |
| | num_examples: 382 |
| | - name: cosmetics |
| | num_bytes: 1565263 |
| | num_examples: 2384 |
| | - name: banking |
| | num_bytes: 446944 |
| | num_examples: 561 |
| | download_size: 8006167 |
| | dataset_size: 4877221 |
| | - config_name: all |
| | features: |
| | - name: id |
| | dtype: int32 |
| | - name: category |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: ner |
| | sequence: |
| | - name: source |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | - name: target |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | splits: |
| | - name: train |
| | num_bytes: 4937658 |
| | num_examples: 5718 |
| | download_size: 8006167 |
| | dataset_size: 4937658 |
| | - config_name: tele |
| | features: |
| | - name: id |
| | dtype: int32 |
| | - name: category |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: ner |
| | sequence: |
| | - name: source |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | - name: target |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | splits: |
| | - name: train |
| | num_bytes: 2758147 |
| | num_examples: 2391 |
| | download_size: 4569708 |
| | dataset_size: 2758147 |
| | - config_name: electro |
| | features: |
| | - name: id |
| | dtype: int32 |
| | - name: category |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: ner |
| | sequence: |
| | - name: source |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | - name: target |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | splits: |
| | - name: train |
| | num_bytes: 130205 |
| | num_examples: 382 |
| | download_size: 269917 |
| | dataset_size: 130205 |
| | - config_name: cosmetics |
| | features: |
| | - name: id |
| | dtype: int32 |
| | - name: category |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: ner |
| | sequence: |
| | - name: source |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | - name: target |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | splits: |
| | - name: train |
| | num_bytes: 1596259 |
| | num_examples: 2384 |
| | download_size: 2417388 |
| | dataset_size: 1596259 |
| | - config_name: banking |
| | features: |
| | - name: id |
| | dtype: int32 |
| | - name: category |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: ner |
| | sequence: |
| | - name: source |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | - name: target |
| | struct: |
| | - name: from |
| | dtype: int32 |
| | - name: text |
| | dtype: string |
| | - name: to |
| | dtype: int32 |
| | - name: type |
| | dtype: |
| | class_label: |
| | names: |
| | '0': PRODUCT_NAME |
| | '1': PRODUCT_NAME_IMP |
| | '2': PRODUCT_NO_BRAND |
| | '3': BRAND_NAME |
| | '4': BRAND_NAME_IMP |
| | '5': VERSION |
| | '6': PRODUCT_ADJ |
| | '7': BRAND_ADJ |
| | '8': LOCATION |
| | '9': LOCATION_IMP |
| | splits: |
| | - name: train |
| | num_bytes: 453119 |
| | num_examples: 561 |
| | download_size: 749154 |
| | dataset_size: 453119 |
| | --- |
| | |
| | # Dataset Card for [Dataset Name] |
| |
|
| | ## Table of Contents |
| | - [Dataset Description](#dataset-description) |
| | - [Dataset Summary](#dataset-summary) |
| | - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| | - [Languages](#languages) |
| | - [Dataset Structure](#dataset-structure) |
| | - [Data Instances](#data-instances) |
| | - [Data Fields](#data-fields) |
| | - [Data Splits](#data-splits) |
| | - [Dataset Creation](#dataset-creation) |
| | - [Curation Rationale](#curation-rationale) |
| | - [Source Data](#source-data) |
| | - [Annotations](#annotations) |
| | - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| | - [Considerations for Using the Data](#considerations-for-using-the-data) |
| | - [Social Impact of Dataset](#social-impact-of-dataset) |
| | - [Discussion of Biases](#discussion-of-biases) |
| | - [Other Known Limitations](#other-known-limitations) |
| | - [Additional Information](#additional-information) |
| | - [Dataset Curators](#dataset-curators) |
| | - [Licensing Information](#licensing-information) |
| | - [Citation Information](#citation-information) |
| | - [Contributions](#contributions) |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** [bprec homepage](https://clarin-pl.eu/dspace/handle/11321/736) |
| | - **Repository:** [bprec repository](https://gitlab.clarin-pl.eu/team-semantics/semrel-extraction) |
| | - **Paper:** [bprec paper](https://www.aclweb.org/anthology/2020.lrec-1.233.pdf) |
| | - **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](https://github.com/kldarek) for adding this dataset. |
