Aitaro Yamamoto


2024

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Arukikata Travelogue Dataset with Geographic Entity Mention, Coreference, and Link Annotation
Shohei Higashiyama | Hiroki Ouchi | Hiroki Teranishi | Hiroyuki Otomo | Yusuke Ide | Aitaro Yamamoto | Hiroyuki Shindo | Yuki Matsuda | Shoko Wakamiya | Naoya Inoue | Ikuya Yamada | Taro Watanabe
Findings of the Association for Computational Linguistics: EACL 2024

Geoparsing is a fundamental technique for analyzing geo-entity information in text, which is useful for geographic applications, e.g., tourist spot recommendation. We focus on document-level geoparsing that considers geographic relatedness among geo-entity mentions and present a Japanese travelogue dataset designed for training and evaluating document-level geoparsing systems. Our dataset comprises 200 travelogue documents with rich geo-entity information: 12,171 mentions, 6,339 coreference clusters, and 2,551 geo-entities linked to geo-database entries.