{"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/symbolic-priors-for-rnn-based-semantic","title":"Symbolic Priors for RNN-based Semantic Parsing","arxiv_id":"1809.07721","date":"2018-09-20","proceeding":null,"authors":["Chunyang Xiao","Marc Dymetman","Claire Gardent"],"abstract":"Seq2seq models based on Recurrent Neural Networks (RNNs) have recently\nreceived a lot of attention in the domain of Semantic Parsing for Question\nAnswering. While in principle they can be trained directly on pairs (natural\nlanguage utterances, logical forms), their performance is limited by the amount\nof available data. To alleviate this problem, we propose to exploit various\nsources of prior knowledge: the well-formedness of the logical forms is modeled\nby a weighted context-free grammar; the likelihood that certain entities\npresent in the input utterance are also present in the logical form is modeled\nby weighted finite-state automata. The grammar and automata are combined\ntogether through an efficient intersection algorithm to form a soft guide\n(\"background\") to the RNN. We test our method on an extension of the Overnight\ndataset and show that it not only strongly improves over an RNN baseline, but\nalso outperforms non-RNN models based on rich sets of hand-crafted features.","url_abs":"http://arxiv.org/abs/1809.07721v1","url_pdf":"http://arxiv.org/pdf/1809.07721v1.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":"symbolic-priors-for-rnn-based-semantic","repo_url":"https://github.com/chunyangx/overnight_more","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"semantic-parsing","task_name":"Semantic Parsing"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}