|
--- |
|
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. |
