TERMinator: A System for Scientific Texts Processing
Elena Bruches, Olga Tikhobaeva, Yana Dementyeva, Tatiana Batura
Abstract
This paper is devoted to the extraction of entities and semantic relations between them from scientific texts, where we consider scientific terms as entities. In this paper, we present a dataset that includes annotations for two tasks and develop a system called TERMinator for the study of the influence of language models on term recognition and comparison of different approaches for relation extraction. Experiments show that language models pre-trained on the target language are not always show the best performance. Also adding some heuristic approaches may improve the overall quality of the particular task. The developed tool and the annotated corpus are publicly available at https://github.com/iis-research-team/terminator and may be useful for other researchers.- Anthology ID:
- 2022.coling-1.302
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 3420–3426
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.302
- DOI:
- Bibkey:
- Cite (ACL):
- Elena Bruches, Olga Tikhobaeva, Yana Dementyeva, and Tatiana Batura. 2022. TERMinator: A System for Scientific Texts Processing. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3420–3426, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- TERMinator: A System for Scientific Texts Processing (Bruches et al., COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.302.pdf
- Data
- SciERC
Export citation
@inproceedings{bruches-etal-2022-terminator,
title = "{TERM}inator: A System for Scientific Texts Processing",
author = "Bruches, Elena and
Tikhobaeva, Olga and
Dementyeva, Yana and
Batura, Tatiana",
editor = "Calzolari, Nicoletta and
Huang, Chu-Ren and
Kim, Hansaem and
Pustejovsky, James and
Wanner, Leo and
Choi, Key-Sun and
Ryu, Pum-Mo and
Chen, Hsin-Hsi and
Donatelli, Lucia and
Ji, Heng and
Kurohashi, Sadao and
Paggio, Patrizia and
Xue, Nianwen and
Kim, Seokhwan and
Hahm, Younggyun and
He, Zhong and
Lee, Tony Kyungil and
Santus, Enrico and
Bond, Francis and
Na, Seung-Hoon",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.302",
pages = "3420--3426",
abstract = "This paper is devoted to the extraction of entities and semantic relations between them from scientific texts, where we consider scientific terms as entities. In this paper, we present a dataset that includes annotations for two tasks and develop a system called TERMinator for the study of the influence of language models on term recognition and comparison of different approaches for relation extraction. Experiments show that language models pre-trained on the target language are not always show the best performance. Also adding some heuristic approaches may improve the overall quality of the particular task. The developed tool and the annotated corpus are publicly available at \url{https://github.com/iis-research-team/terminator} and may be useful for other researchers.",
}
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%0 Conference Proceedings %T TERMinator: A System for Scientific Texts Processing %A Bruches, Elena %A Tikhobaeva, Olga %A Dementyeva, Yana %A Batura, Tatiana %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F bruches-etal-2022-terminator %X This paper is devoted to the extraction of entities and semantic relations between them from scientific texts, where we consider scientific terms as entities. In this paper, we present a dataset that includes annotations for two tasks and develop a system called TERMinator for the study of the influence of language models on term recognition and comparison of different approaches for relation extraction. Experiments show that language models pre-trained on the target language are not always show the best performance. Also adding some heuristic approaches may improve the overall quality of the particular task. The developed tool and the annotated corpus are publicly available at https://github.com/iis-research-team/terminator and may be useful for other researchers. %U https://aclanthology.org/2022.coling-1.302 %P 3420-3426
Markdown (Informal)
[TERMinator: A System for Scientific Texts Processing](https://aclanthology.org/2022.coling-1.302) (Bruches et al., COLING 2022)
- TERMinator: A System for Scientific Texts Processing (Bruches et al., COLING 2022)
ACL
- Elena Bruches, Olga Tikhobaeva, Yana Dementyeva, and Tatiana Batura. 2022. TERMinator: A System for Scientific Texts Processing. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3420–3426, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.