{"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/sequence-to-action-end-to-end-semantic-graph","title":"Sequence-to-Action: End-to-End Semantic Graph Generation for Semantic Parsing","arxiv_id":"1809.00773","date":"2018-09-04","proceeding":"ACL 2018 7","authors":["Bo Chen","Le Sun","Xianpei Han"],"abstract":"This paper proposes a neural semantic parsing approach -- Sequence-to-Action,\nwhich models semantic parsing as an end-to-end semantic graph generation\nprocess. Our method simultaneously leverages the advantages from two recent\npromising directions of semantic parsing. Firstly, our model uses a semantic\ngraph to represent the meaning of a sentence, which has a tight-coupling with\nknowledge bases. Secondly, by leveraging the powerful representation learning\nand prediction ability of neural network models, we propose a RNN model which\ncan effectively map sentences to action sequences for semantic graph\ngeneration. Experiments show that our method achieves state-of-the-art\nperformance on OVERNIGHT dataset and gets competitive performance on GEO and\nATIS datasets.","url_abs":"http://arxiv.org/abs/1809.00773v1","url_pdf":"http://arxiv.org/pdf/1809.00773v1.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":[{"paper_slug":"sequence-to-action-end-to-end-semantic-graph","repo_url":"https://github.com/dongpobeyond/Seq2Act","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"graph-generation","task_name":"Graph Generation"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"semantic-parsing","task_name":"Semantic Parsing"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1809.00773","atlas_url":"https://app.syntology.ai/?focus=1809.00773","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}