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---
language:
- ru
multilinguality:
- monolingual
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: RuREBus
---
# RuREBus dataset
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Structure](#dataset-structure)
- [Citation Information](#citation-information)
- [Contacts](#contacts)
## Dataset Description
RuREBus dataset (https://github.com/dialogue-evaluation/RuREBus) is
a Russian dataset for named entity recognition and relation extraction.
## Dataset Structure
There are two subsets of the dataset.
Using
`load_dataset('MalakhovIlya/RuREBus')`
you can download annotated data (DatasetDict) for named entity recognition task and
relation extraction tasks.
This subset consists of two splits: "train" and "test".
Using
`load_dataset('MalakhovIlya/NEREL', 'raw_txt')['raw_txt']`
you can download (Dataset) large corpus (~3gb) raw texts of the same subject
area, but without any annotations.
"entities" are used in named-entity recognition task (see https://en.wikipedia.org/wiki/Named-entity_recognition).
"relations" are used in relationship extraction task (see https://en.wikipedia.org/wiki/Relationship_extraction).
Each entity is represented by a string of the following format:
`"<id>\t<type> <start> <stop>\t<text>"`, where
`<id>` is an entity id,
`<type>` is one of entity types,
`<start>` is a position of the first symbol of entity in text,
`<stop>` is the last symbol position in text +1.
Each relation is represented by a string of the following format:
`"<id>\t<type> Arg1:<arg1_id> Arg2:<arg2_id>"`, where
`<id>` is a relation id,
`<arg1_id>` and `<arg2_id>` are entity ids.
## Citation Information
@inproceedings{rurebus,
Address = {Moscow, Russia},
Author = {Ivanin, Vitaly and Artemova, Ekaterina and Batura, Tatiana and Ivanov, Vladimir and Sarkisyan, Veronika and Tutubalina, Elena and Smurov, Ivan},
Title = {RuREBus-2020 Shared Task: Russian Relation Extraction for Business},
Booktitle = {Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference “Dialog” [Komp’iuternaia Lingvistika i Intellektual’nye Tehnologii: Trudy Mezhdunarodnoj Konferentsii “Dialog”]},
Year = {2020}
}
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