Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
other
Source Datasets:
extended|other
ArXiv:
License:
| annotations_creators: | |
| - other | |
| language: | |
| - en | |
| language_creators: | |
| - found | |
| license: | |
| - other | |
| multilinguality: | |
| - monolingual | |
| pretty_name: KBP37 is an English Relation Classification dataset | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - extended|other | |
| tags: | |
| - relation extraction | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - multi-class-classification | |
| dataset_info: | |
| - config_name: kbp37 | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: sentence | |
| dtype: string | |
| - name: relation | |
| dtype: | |
| class_label: | |
| names: | |
| '0': no_relation | |
| '1': org:alternate_names(e1,e2) | |
| '2': org:alternate_names(e2,e1) | |
| '3': org:city_of_headquarters(e1,e2) | |
| '4': org:city_of_headquarters(e2,e1) | |
| '5': org:country_of_headquarters(e1,e2) | |
| '6': org:country_of_headquarters(e2,e1) | |
| '7': org:founded(e1,e2) | |
| '8': org:founded(e2,e1) | |
| '9': org:founded_by(e1,e2) | |
| '10': org:founded_by(e2,e1) | |
| '11': org:members(e1,e2) | |
| '12': org:members(e2,e1) | |
| '13': org:stateorprovince_of_headquarters(e1,e2) | |
| '14': org:stateorprovince_of_headquarters(e2,e1) | |
| '15': org:subsidiaries(e1,e2) | |
| '16': org:subsidiaries(e2,e1) | |
| '17': org:top_members/employees(e1,e2) | |
| '18': org:top_members/employees(e2,e1) | |
| '19': per:alternate_names(e1,e2) | |
| '20': per:alternate_names(e2,e1) | |
| '21': per:cities_of_residence(e1,e2) | |
| '22': per:cities_of_residence(e2,e1) | |
| '23': per:countries_of_residence(e1,e2) | |
| '24': per:countries_of_residence(e2,e1) | |
| '25': per:country_of_birth(e1,e2) | |
| '26': per:country_of_birth(e2,e1) | |
| '27': per:employee_of(e1,e2) | |
| '28': per:employee_of(e2,e1) | |
| '29': per:origin(e1,e2) | |
| '30': per:origin(e2,e1) | |
| '31': per:spouse(e1,e2) | |
| '32': per:spouse(e2,e1) | |
| '33': per:stateorprovinces_of_residence(e1,e2) | |
| '34': per:stateorprovinces_of_residence(e2,e1) | |
| '35': per:title(e1,e2) | |
| '36': per:title(e2,e1) | |
| splits: | |
| - name: train | |
| num_bytes: 3570626 | |
| num_examples: 15917 | |
| - name: validation | |
| num_bytes: 388935 | |
| num_examples: 1724 | |
| - name: test | |
| num_bytes: 762806 | |
| num_examples: 3405 | |
| download_size: 5106673 | |
| dataset_size: 4722367 | |
| - config_name: kbp37_formatted | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: token | |
| sequence: string | |
| - name: e1_start | |
| dtype: int32 | |
| - name: e1_end | |
| dtype: int32 | |
| - name: e2_start | |
| dtype: int32 | |
| - name: e2_end | |
| dtype: int32 | |
| - name: relation | |
| dtype: | |
| class_label: | |
| names: | |
| '0': no_relation | |
| '1': org:alternate_names(e1,e2) | |
| '2': org:alternate_names(e2,e1) | |
| '3': org:city_of_headquarters(e1,e2) | |
| '4': org:city_of_headquarters(e2,e1) | |
| '5': org:country_of_headquarters(e1,e2) | |
| '6': org:country_of_headquarters(e2,e1) | |
| '7': org:founded(e1,e2) | |
| '8': org:founded(e2,e1) | |
| '9': org:founded_by(e1,e2) | |
| '10': org:founded_by(e2,e1) | |
| '11': org:members(e1,e2) | |
| '12': org:members(e2,e1) | |
| '13': org:stateorprovince_of_headquarters(e1,e2) | |
| '14': org:stateorprovince_of_headquarters(e2,e1) | |
| '15': org:subsidiaries(e1,e2) | |
| '16': org:subsidiaries(e2,e1) | |
| '17': org:top_members/employees(e1,e2) | |
| '18': org:top_members/employees(e2,e1) | |
| '19': per:alternate_names(e1,e2) | |
| '20': per:alternate_names(e2,e1) | |
| '21': per:cities_of_residence(e1,e2) | |
| '22': per:cities_of_residence(e2,e1) | |
| '23': per:countries_of_residence(e1,e2) | |
| '24': per:countries_of_residence(e2,e1) | |
| '25': per:country_of_birth(e1,e2) | |
| '26': per:country_of_birth(e2,e1) | |
| '27': per:employee_of(e1,e2) | |
| '28': per:employee_of(e2,e1) | |
| '29': per:origin(e1,e2) | |
| '30': per:origin(e2,e1) | |
| '31': per:spouse(e1,e2) | |
| '32': per:spouse(e2,e1) | |
| '33': per:stateorprovinces_of_residence(e1,e2) | |
| '34': per:stateorprovinces_of_residence(e2,e1) | |
| '35': per:title(e1,e2) | |
| '36': per:title(e2,e1) | |
| splits: | |
| - name: train | |
| num_bytes: 4943394 | |
| num_examples: 15807 | |
| - name: validation | |
| num_bytes: 539197 | |
| num_examples: 1714 | |
| - name: test | |
| num_bytes: 1055918 | |
| num_examples: 3379 | |
| download_size: 5106673 | |
| dataset_size: 6581345 | |
| # Dataset Card for "kbp37" | |
| ## Table of Contents | |
| - [Table of Contents](#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:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Repository:** [kbp37](https://github.com/zhangdongxu/kbp37) | |
| - **Paper:** [Relation Classification via Recurrent Neural Network](https://arxiv.org/abs/1508.01006) | |
| - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Size of downloaded dataset files:** 5.11 MB | |
| - **Size of the generated dataset:** 6.58 MB | |
| ### Dataset Summary | |
| KBP37 is a revision of MIML-RE annotation dataset, provided by Gabor Angeli et al. (2014). They use both the 2010 and | |
| 2013 KBP official document collections, as well as a July 2013 dump of Wikipedia as the text corpus for annotation. | |
| There are 33811 sentences been annotated. Zhang and Wang made several refinements: | |
| 1. They add direction to the relation names, e.g. '`per:employee_of`' is split into '`per:employee of(e1,e2)`' | |
| and '`per:employee of(e2,e1)`'. They also replace '`org:parents`' with '`org:subsidiaries`' and replace | |
| '`org:member of’ with '`org:member`' (by their reverse directions). | |
| 2. They discard low frequency relations such that both directions of each relation occur more than 100 times in the | |
| dataset. | |
| KBP37 contains 18 directional relations and an additional '`no_relation`' relation, resulting in 37 relation classes. | |
| Note: | |
| - There is a formatted version that you can load with `datasets.load_dataset('kbp37', name='kbp37_formatted')`. This version is tokenized with `str.split()` and | |
| provides entities as offsets instead of being enclosed by xml tags. It discards some examples, however, that are invalid in the original dataset and lead | |
| to entity offset errors, e.g. example train/1276. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Languages | |
| The language data in KBP37 is in English (BCP-47 en) | |
| ## Dataset Structure | |
| ### Data Instances | |
| #### kbp37 | |
| - **Size of downloaded dataset files:** 5.11 MB | |
| - **Size of the generated dataset:** 4.7 MB | |
| An example of 'train' looks as follows: | |
| ```json | |
| { | |
| "id": "0", | |
| "sentence": "<e1> Thom Yorke </e1> of <e2> Radiohead </e2> has included the + for many of his signature distortion sounds using a variety of guitars to achieve various tonal options .", | |
| "relation": 27 | |
| } | |
| ``` | |
| #### kbp37_formatted | |
| - **Size of downloaded dataset files:** 5.11 MB | |
| - **Size of the generated dataset:** 6.58 MB | |
| An example of 'train' looks as follows: | |
| ```json | |
| { | |
| "id": "1", | |
| "token": ["Leland", "High", "School", "is", "a", "public", "high", "school", "located", "in", "the", "Almaden", "Valley", "in", "San", "Jose", "California", "USA", "in", "the", "San", "Jose", "Unified", "School", "District", "."], | |
| "e1_start": 0, | |
| "e1_end": 3, | |
| "e2_start": 14, | |
| "e2_end": 16, | |
| "relation": 3 | |
| } | |
| ``` | |
| ### Data Fields | |
| #### kbp37 | |
| - `id`: the instance id of this sentence, a `string` feature. | |
| - `sentence`: the sentence, a `string` features. | |
| - `relation`: the relation label of this instance, an `int` classification label. | |
| ```python | |
| {"no_relation": 0, "org:alternate_names(e1,e2)": 1, "org:alternate_names(e2,e1)": 2, "org:city_of_headquarters(e1,e2)": 3, "org:city_of_headquarters(e2,e1)": 4, "org:country_of_headquarters(e1,e2)": 5, "org:country_of_headquarters(e2,e1)": 6, "org:founded(e1,e2)": 7, "org:founded(e2,e1)": 8, "org:founded_by(e1,e2)": 9, "org:founded_by(e2,e1)": 10, "org:members(e1,e2)": 11, "org:members(e2,e1)": 12, "org:stateorprovince_of_headquarters(e1,e2)": 13, "org:stateorprovince_of_headquarters(e2,e1)": 14, "org:subsidiaries(e1,e2)": 15, "org:subsidiaries(e2,e1)": 16, "org:top_members/employees(e1,e2)": 17, "org:top_members/employees(e2,e1)": 18, "per:alternate_names(e1,e2)": 19, "per:alternate_names(e2,e1)": 20, "per:cities_of_residence(e1,e2)": 21, "per:cities_of_residence(e2,e1)": 22, "per:countries_of_residence(e1,e2)": 23, "per:countries_of_residence(e2,e1)": 24, "per:country_of_birth(e1,e2)": 25, "per:country_of_birth(e2,e1)": 26, "per:employee_of(e1,e2)": 27, "per:employee_of(e2,e1)": 28, "per:origin(e1,e2)": 29, "per:origin(e2,e1)": 30, "per:spouse(e1,e2)": 31, "per:spouse(e2,e1)": 32, "per:stateorprovinces_of_residence(e1,e2)": 33, "per:stateorprovinces_of_residence(e2,e1)": 34, "per:title(e1,e2)": 35, "per:title(e2,e1)": 36} | |
| ``` | |
| #### kbp37_formatted | |
| - `id`: the instance id of this sentence, a `string` feature. | |
| - `token`: the list of tokens of this sentence, using `str.split()`, a `list` of `string` features. | |
| - `e1_start`: the 0-based index of the start token of the first argument', an `int` feature. | |
| - `e1_end`: the 0-based index of the end token of the first argument, exclusive, an `int` feature. | |
| - `e2_start`: the 0-based index of the start token of the second argument, an `int` feature. | |
| - `e2_end`: the 0-based index of the end token of the second argument, exclusive, an `int` feature. | |
| - `relation`: the relation label of this instance, an `int` classification label (same as `'kbp37''`). | |
| ### Data Splits | |
| | | Train | Dev | Test | | |
| |-------|-------|------|------| | |
| | kbp37 | 15917 | 1724 | 3405 | | |
| | kbp37_formatted | 15807 | 1714 | 3379 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the source language producers? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the annotators? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Personal and Sensitive Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Discussion of Biases | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Other Known Limitations | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Licensing Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Citation Information | |
| ``` | |
| @article{DBLP:journals/corr/ZhangW15a, | |
| author = {Dongxu Zhang and | |
| Dong Wang}, | |
| title = {Relation Classification via Recurrent Neural Network}, | |
| journal = {CoRR}, | |
| volume = {abs/1508.01006}, | |
| year = {2015}, | |
| url = {http://arxiv.org/abs/1508.01006}, | |
| eprinttype = {arXiv}, | |
| eprint = {1508.01006}, | |
| timestamp = {Fri, 04 Nov 2022 18:37:50 +0100}, | |
| biburl = {https://dblp.org/rec/journals/corr/ZhangW15a.bib}, | |
| bibsource = {dblp computer science bibliography, https://dblp.org} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@phucdev](https://github.com/phucdev) for adding this dataset. |