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Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning
https://repository.ninjal.ac.jp/records/3283
https://repository.ninjal.ac.jp/records/32838017be6d-8b5a-46bd-afd8-7dab1ee1182f
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
2020.findings-emnlp.121.pdf (500.6 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2021-03-26 | |||||
| タイトル | ||||||
| タイトル | Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| 著者 |
Cheng, Fei
× Cheng, Fei× Asahara, Masayuki× Kobayashi, Ichiro× Kurohashi, Sadao |
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| 著者所属(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Kyoto University | |||||
| 著者所属(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | National Institute for Japanese Language and Linguistics | |||||
| 著者所属(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Ochanomizu University | |||||
| 著者所属(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Kyoto University | |||||
| 抄録(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Temporal relation classification is a pair-wise task for identifying the relation of a temporal link (TLINK) between two mentions, i.e. event, time and document creation time (DCT). It leads to two crucial limits: 1) Two TLINKs involving a common mention do not share information. 2) Existing models with independent classifiers for each TLINK category (E2E, E2T and E2D) hinder from using the whole data. This paper presents an event centric model that allows to manage dynamic event representations across multiple TLINKs. Our model deals with three TLINK categories with multi-task learning to leverage the full size of data. The experimental results show that our proposal outperforms state-of-the-art models and two transfer learning baselines on both the English and Japanese data. | |||||
| 出版者 | ||||||
| 出版者 | Association for Computational Linguistics | |||||
| 書誌情報 |
en : Findings of the Association for Computational Linguistics: EMNLP 2020 p. 1352-1357, 発行日 2020-11 |
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| DOI | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.18653/v1/2020.findings-emnlp.121 | |||||
| フォーマット | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | application/pdf | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
