{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/semantic-relation-classification-via-2","title":"Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling","arxiv_id":"1506.07650","date":"2015-06-25","proceeding":"EMNLP 2015 9","authors":["Kun Xu","Yansong Feng","Songfang Huang","Dongyan Zhao"],"abstract":"Syntactic features play an essential role in identifying relationship in a\nsentence. Previous neural network models often suffer from irrelevant\ninformation introduced when subjects and objects are in a long distance. In\nthis paper, we propose to learn more robust relation representations from the\nshortest dependency path through a convolution neural network. We further\npropose a straightforward negative sampling strategy to improve the assignment\nof subjects and objects. Experimental results show that our method outperforms\nthe state-of-the-art methods on the SemEval-2010 Task 8 dataset.","url_abs":"http://arxiv.org/abs/1506.07650v1","url_pdf":"http://arxiv.org/pdf/1506.07650v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":null,"task_name":"Relation"},{"task_slug":"relation-classification","task_name":"Relation Classification"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/relation-classification-on-semeval-2010-task-1","task":"Relation Classification","dataset":"SemEval 2010 Task 8","model":"depLCNN + NS","rank_in_archive_order":3,"of":6,"metrics":{"F1":"85.6"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1506.07650","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}