{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:37:51Z","timestamp":1761176271939,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Spatial relation extraction is to identify the spatial positions and dynamic relations between geographical entities within a given text. Previous research has been hindered by two significant challenges: extracting null-role and multi-mention relations. Null-role relations frequently lack the requisite spatial elements to fully express their semantics, while multi-mention relations may confuse models due to the presence of non-coreferent repeated elements within a sentence. To address the two above issues, we propose a prompt-based method that integrates null-role-specific templates and element markers to enhance the encoding process and subsequently improve the model\u2019s discriminative ability. The experimental results on the SpaceEval dataset demonstrate that our proposed model outperforms the SOTA baselines significantly, particularly in terms of its ability to handle null-role and multi-mention relations.<\/jats:p>","DOI":"10.3233\/faia251325","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:58:12Z","timestamp":1761127092000},"source":"Crossref","is-referenced-by-count":0,"title":["Spatial Relation Extraction on Null-Role and Multi-Mention Relation Templates"],"prefix":"10.3233","author":[{"given":"Yuming","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, Suzhou, China"}]},{"given":"Peifeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, Suzhou, China"}]},{"given":"Qiaoming","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, Suzhou, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251325","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:58:12Z","timestamp":1761127092000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251325"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251325","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}