Kazan Federal University Digital Repository

Rurebus-2020 shared task: Russian relation extraction for business

Show simple item record

dc.contributor.author Ivanin V.A.
dc.contributor.author Artemova E.L.
dc.contributor.author Batura T.V.
dc.contributor.author Ivanov V.V.
dc.contributor.author Sarkisyan V.V.
dc.contributor.author Tutubalina E.V.
dc.contributor.author Smurov I.M.
dc.date.accessioned 2021-02-25T06:56:03Z
dc.date.available 2021-02-25T06:56:03Z
dc.date.issued 2020
dc.identifier.issn 2221-7932
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/161571
dc.description.abstract © 2020 ABBYY PRODUCTION LLC. All rights reserved. In this paper, we present a shared task on core information extraction problems, named entity recognition and relation extraction. In contrast to popular shared tasks on related problems, we try to move away from strictly academic rigor and rather model a business case. As a source for textual data we choose the corpus of Russian strategic documents, which we annotated according to our own annotation scheme. To speed up the annotation process, we exploit various active learning techniques. In total we ended up with more than two hundred annotated documents. Thus we managed to create a high-quality data set in short time. The shared task consisted of three tracks, devoted to 1) named entity recognition, 2) relation extraction and 3) joint named entity recognition and relation extraction. We provided with the annotated texts as well as a set of unannotated texts, which could of been used in any way to improve solutions. In the paper we overview and compare solutions, submitted by the shared task participants. We release both raw and annotated corpora along with annotation guidelines, evaluation scripts and results at https://github.com/dialogue-evaluation/RuREBus.
dc.relation.ispartofseries Komp'juternaja Lingvistika i Intellektual'nye Tehnologii
dc.subject BERT
dc.subject Named entity recognition
dc.subject Relation extraction
dc.subject Russian fine-tuning
dc.subject Shared task
dc.title Rurebus-2020 shared task: Russian relation extraction for business
dc.type Conference Paper
dc.relation.ispartofseries-issue 19
dc.relation.ispartofseries-volume 2020-June
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 416
dc.source.id SCOPUS22217932-2020-2020-19-SID85093820206


Files in this item

This item appears in the following Collection(s)

  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

Show simple item record

Search DSpace


Advanced Search

Browse

My Account

Statistics