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RENERSANs: Relation Extraction and Named Entity Recognition as Sequence Annotation
P. 187–197.
Davletov A., Gordeev D., Rei A., Arefyev N.
In this work we present our system for RuREBus shared task held together with Dialog 2020 conference. The task consisted of 3 subtasks: named entity recognition, relation extraction with provided named entity tags and end-to-end relation extraction. Our system took the first and the second place in the first and the second subtasks respectively. For the third subtask we submitted our solution only in the post-evaluation phase, however, it was among the top 2 best performing systems. The systems for all tasks are based on Transformer models. Relation extraction was solved as a sequence labelling problem. We also used joint task named entity and relation extraction learning.
Publication based on the results of:
In book
Селегей В. Issue 19(26): дополнительный том. , -, 2020.
Kolmogorova A., Зарембо В. С., Ткачева Е. С. et al., В кн.: Лингвистическая семантика в пространственном измерении: Словарь. Дискурс. Корпус.: Екатеринбург: Кабинетный ученый, 2024. Гл. 10 С. 423–445.
The purpose of this study is to describe the characteristics of the text of a popular Soviet song as a linguo-ideological phenomenon. The corpus of Soviet songs collected by the research group is used as material. The focus of this publication is on two characteristics: changes in the emotional tonality of popular songs released on ...
Added: December 10, 2023
Loukachevitch N., Manandhar S., Baral E. et al., Bioinformatics 2023 Vol. 39 No. 4 Article btad161
Motivation
This paper describes NEREL-BIO – an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain dataset NEREL (Loukachevitch et al., 2021) by introducing domain-specific entity types. NEREL-BIO annotation scheme covers both general and biomedical domains making it suitable for domain transfer experiments. NEREL-BIO ...
Added: April 5, 2023
Soshnikov D. V., Soshnikova V., / Series Computer Science "arxiv.org". 2021.
Since the beginning of COVID pandemic, there have been around 700000 scientific papers published on the subject. A human researcher cannot possibly get acquainted with such a huge text corpus -- and therefore developing AI-based tools to help navigating this corpus and deriving some useful insights from it is highly needed. In this paper, we ...
Added: February 22, 2022
Loukachevitch N., Artemova E., Batura T. et al., , in: International Conference Recent Advances in Natural Language Processing, RANLP 2021.: Association for Computational Linguistics, 2021. P. 876–886.
In this paper, we present NEREL, a Rus- sian dataset for named entity recognition and relation extraction. NEREL is significantly larger than existing Russian datasets: to date it contains 56K annotated named entities and 39K annotated relations. Its important dif- ference from previous datasets is annotation of nested named entities, as well as relations within ...
Added: September 27, 2021
Efim Luboshnikov, Makarov I., , in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary ProceedingsVol. 12602.: Springer, 2021. Ch. 8 P. 90–101.
This article is devoted to the implementation of the federated approach to named entity recognition. The novel federated approach is designed to solve data privacy issues. The classic BiLSTM-CNNs-CRF and its modifications trained on a single machine are taken as baseline. Federated training is conducted for them. Influence of use of pretrained embedding, use of ...
Added: March 24, 2021
Nikiforovskaya A., Kapralov N., Vlasova A. et al., , in: 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA 2020).: Miami: IEEE, 2020. P. 314–319.
With an ever-increasing number of scientific papers published each year, it becomes more difficult for researchers to explore a field that they are not closely familiar with already. This greatly inhibits the potential for cross-disciplinary research. A traditional introduction into an area may come in the form of a review paper. However, not all areas ...
Added: December 28, 2020
Shavrina T., Fenogenova A., Emelyanov A. et al., , in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).: Association for Computational Linguistics, 2020. P. 4717–4726.
Added: November 22, 2020
Emelyanov A., Artemova E., , in: Computational Linguistics and Intellectual Technologies Papers from the Annual International Conference “Dialogue” (2019)Issue 18.: M.: Russian State University for the Humanitie, 2019. P. 203–212.
The article is devoted to the problem of automatic gapping resolution for the Russian language. We use BERT Language Model as embeddings with bidirectional recurrent net- work, attention, and NCRF on the top. Unlike other models these are using BERT, we apply BERT only as embedder without any fine-tuning. As a result, our implementation took ...
Added: October 29, 2020
Ivanin V., Artemova E., Batura T. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: по материалам ежегодной международной конференции «Диалог» (Москва, 17–20 июня 2020 г.)Issue 19(26): дополнительный том.: -, 2020. P. 401–416.
In this paper, we present a shared task on core information extraction prob- lems, named entity recognition and relation extraction. In contrast to popular shared tasks on related problems, we try to move away from strictly aca- demic rigor and rather model a business case. As a source for textual data we choose the corpus ...
Added: June 21, 2020
Artemova E., Batura T., Sarkisyan V. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 416–432.
В статье представлены результаты соревнования по распознаванию именованных сущностей и извлечению отношений. Целью соревнования является сравнение методов извлечения сущностей и отношений на русском языке в постановке, приближенной к индустриальным задачам. В качестве исходной коллекции текстов использовался корпус Минэкономразвития РФ, содержащий программы стратегического развития. Корпус был размечен в соответствии с инструкцией, разработанной авторами статьи. В процессе ...
Added: June 11, 2020
Knutov A., Styrin E. M., , in: Beyond Smart and Connected Governments Sensors and the Internet of Things in the Public Sector.: Springer, 2020. Ch. 7 P. 139–164.
The Internet of Things is being actively introduced in Russian public governance for inspection and oversight. In this chapter, based on an analysis of IoT policy, legal acts, secondary statistical data, and the authors’ own involvement in testing IoT technologies, we formulate cases and use them as a basis for an IoT classification oriented to ...
Added: May 5, 2020
Emelyanov A., Artemova E., , in: Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing, 2019, Florence, Italy, Association for Computational Linguistics.: Association for Computational Linguistics, 2019. P. 94–99.
In this paper we tackle multilingual named entity recognition task. We use the BERT Language Model as embeddings with bidirectional recurrent network, attention, and NCRF on the top. We apply multilingual BERT only as embedder without any fine-tuning. We test out model on the dataset of the BSNLP shared task, which consists of texts in ...
Added: October 31, 2019
Козеренко Е. Б., Кузнецов К. И., Romanov D. A., Информатика и ее применения 2018 Т. 12 № 3 С. 91–98
The paper presents the method for creation of knowledge extraction systems based on the approach employing the software tool system PullEnti comprising the algorithms for morphological and semantic-syntactical analysis which makes it possible to extract entities of certain types from natural language texts (persons, organizations, locations, and other target semantic objects). The PullEnti system uses ...
Added: December 19, 2018
Kuzminov I., Meissner D., Lavrynenko A. S. et al., / NRU Higher School of Economics. Series WP BRP "Science, Technology and Innovation". 2018. No. 78/STI/2018.
The paper analyses problems associated with technologies classification for the purposes of futures studies, in order to ensure definitive inclusion of technologies in specific classes/types when conventional approaches to classification are applied. The evolution of classification approaches in the scope of science philosophy is shortly reviewed, together with the latest research on expert-based and computerised ...
Added: January 22, 2018
Starostin A. S., Bocharov V. V., Alexeeva S. V. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва,1–4 июля 2016 г.)Вып. 15.: М.: Изд-во РГГУ, 2016. P. 688–705.
In this paper, we describe the rules and results of the FactRuEval informa- tion extraction competition held in 2016 as part of the Dialogue Evaluation initiative in the run-up to Dialogue 2016. The systems were to extract in- formation from Russian texts and competed in two named entity extraction tracks and one fact extraction track. ...
Added: October 7, 2016
Leksin V., Nikolenko S. I., , in: Proceedings of the 6th International Conference on Similarity Search and Applications (SISAP 2013), Lecture Notes in Computer ScienceVol. 8199.: Berlin, Heidelberg: Springer, 2013. P. 206–212.
An important characteristic feature of recommender systems for web pages is the abundance of textual information in and about the items being recommended (web pages). To improve recommendations and enhance user experience, we propose to use automatic tag (keyword) extraction for web pages entering the recommender system. We present a novel tag extraction algorithm that ...
Added: September 27, 2013
Golechkova T. Y., Shemyakina V. I., Klepko E. Y., M.: Sputnik+, 2010.
This book presents a course of English for Specific Purposes devoted specifically to the widely-discussed topic Web 2.0. It covers several aspects of online communication ranging from online friendship to business interacions. The activities presented in the coursebook are aimed at developing students’ communicative competence in both written and oral discourse. Web 2.0 includes a ...
Added: March 6, 2013