Rule-based Normalization of Relative Temporal Information (상대적인 시간정보의 규칙기반 정규화)

Young-Seob Jeong (정영섭); Chae-Gyun Lim (임채균); SeungDong Lee (이승동); Medard Edmund Mswahili (메다드); Goodwill Erasmo Ndomba (굿윌돔바); Ho-Jin Choi (최호진)

doi:10.9708/jksci.2022.27.12.041

Rule-based Normalization of Relative Temporal Information

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2022, 27(12), pp.41-49
DOI : 10.9708/jksci.2022.27.12.041
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : November 14, 2022
Accepted : December 5, 2022
Published : December 30, 2022

Young-Seob Jeong ¹, Chae-Gyun Lim ², SeungDong Lee ¹, Medard Edmund Mswahili ¹, Goodwill Erasmo Ndomba ¹, Ho-Jin Choi ²

¹충북대학교
²한국과학기술원

Accredited

ABSTRACT

Documents often contain relative time expressions, and it is important to define a schema of the relative time information and develop a system that extracts such information from corpus. In this study, to deal with the relative time expressions, we propose seven additional attributes of timex3: year, month, day, week, hour, minute, and second. We propose a way to represent normalized values of the relative time expressions such as before, after, and count, and also design a set of rules to extract the relative time information from texts. With a new corpus constructed using the new attributes that consists of dialog, news, and history documents, we observed that our rule-set generally achieved 70% accuracy on the 1,041 documents. Especially, with the most frequently appeared attributes such as year, day, and week, we got higher accuracies compared to other attributes. The results of this study, our proposed timex3 attributes and the rule-set, will be useful in the development of services such as question-answer systems and chatbots.

KEYWORDS

Time information, Timex3, Relative temporal information, Normalization, Information extraction, Rule-based

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* References for papers published after 2023 are currently being built.

[web] / Naver Clova / https://clova.ai/ko

[web] / KT Giga gini / https://gigagenie.kt.com/ltemain.do

[web] / IBM Watson / https://www.ibm.com/watson

[confproc] James Pustejovsky / 2010 / ISO-TimeML: An International Standard for Semantic Annotation / Proceedings of the Seventh International Conference on Language Resources and Evaluation : 394~397

[journal] 유현조 / 2011 / A Study of Event and Temporal Information in Korean Text / 언어와 정보 / 한국언어정보학회 15(1) : 31~62

[confproc] Young-Seob Jeong / 2016 / Korean TimeML and Korean TimeBank / Proceedings of the Tenth International Conference on Language Resources and Evaluation : 356~359

[confproc] Tommaso Caselli / 2011 / Annotating Events, Temporal Expressions and Relations in Italian: the It-Timeml Experience for the Ita-TimeBank / Proceedings of the 5th Linguistic Annotation Workshop : 143~151

[confproc] Arman Cohan / 2019 / Pretrained Language Models for Sequential Sentence Classification / Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing : 3693~3699

[confproc] Gati L. Martin / 2022 / SwahBERT: Language Model of Swahili / Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics : 314~324

[confproc] Devendra Singh Sachan / 2018 / Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition / Proceedings of the Machine Learning for Healthcare Conference : 383~402

[journal] Touseef Iqbal / 2020 / The survey: Text generation models in deep learning / Journal of King Saud University -Computer and Information Sciences 34(6) : 2515~2528

[other] Chitwan Saharia / 2022 / Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

[other] Alec Radford / 2022 / Robust Speech Recognition via Large-Scale Weak Supervision

[confproc] Ashish Vaswani / 2017 / Attention Is All You Need / Proceedings of the 31st Conference on Neural Information Processing Systems

[other] Aitor Lewkowycz / 2022 / Solving Quantitative Reasoning Problems with Language Models

[web] / ISO 8601 / https://www.iso.org/iso-8601-date-and-time-format.html

[confproc] Young-Seob Jeong / 2015 / Temporal Information Extraction from Korean Texts / Proceedings of the 19th SIGNLL Conference on Computational Natural Language Learning : 279~288

This paper was written with support from the National Research Foundation of Korea.

KJCKorea
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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Rule-based Normalization of Relative Temporal Information

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* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Rule-based Normalization of Relative Temporal Information

ABSTRACT

KEYWORDS

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