Datasets:
Tasks:
Text Retrieval
Sub-tasks:
entity-linking-retrieval
Languages:
Polish
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
| 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. |