{"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/compositional-sequence-labeling-models-for","title":"Compositional Sequence Labeling Models for Error Detection in Learner Writing","arxiv_id":"1607.06153","date":"2016-07-20","proceeding":"ACL 2016 8","authors":["Marek Rei","Helen Yannakoudakis"],"abstract":"In this paper, we present the first experiments using neural network models\nfor the task of error detection in learner writing. We perform a systematic\ncomparison of alternative compositional architectures and propose a framework\nfor error detection based on bidirectional LSTMs. Experiments on the CoNLL-14\nshared task dataset show the model is able to outperform other participants on\ndetecting errors in learner writing. Finally, the model is integrated with a\npublicly deployed self-assessment system, leading to performance comparable to\nhuman annotators.","url_abs":"http://arxiv.org/abs/1607.06153v1","url_pdf":"http://arxiv.org/pdf/1607.06153v1.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":"grammatical-error-detection","task_name":"Grammatical Error Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/grammatical-error-detection-on-conll-2014-a1","task":"Grammatical Error Detection","dataset":"CoNLL-2014 A1","model":"Bi-LSTM (unrestricted data)","rank_in_archive_order":3,"of":8,"metrics":{"F0.5":"34.3 "},"uses_additional_data":false},{"leaderboard":"/sota/grammatical-error-detection-on-conll-2014-a1","task":"Grammatical Error Detection","dataset":"CoNLL-2014 A1","model":"Bi-LSTM (trained on FCE)","rank_in_archive_order":8,"of":8,"metrics":{"F0.5":"16.4"},"uses_additional_data":false},{"leaderboard":"/sota/grammatical-error-detection-on-conll-2014-a2","task":"Grammatical Error Detection","dataset":"CoNLL-2014 A2","model":"Bi-LSTM (unrestricted data)","rank_in_archive_order":3,"of":8,"metrics":{"F0.5":"44.0"},"uses_additional_data":false},{"leaderboard":"/sota/grammatical-error-detection-on-conll-2014-a2","task":"Grammatical Error Detection","dataset":"CoNLL-2014 A2","model":"Bi-LSTM (trained on FCE)","rank_in_archive_order":8,"of":8,"metrics":{"F0.5":"23.9"},"uses_additional_data":false},{"leaderboard":"/sota/grammatical-error-detection-on-fce","task":"Grammatical Error Detection","dataset":"FCE","model":"Bi-LSTM","rank_in_archive_order":8,"of":8,"metrics":{"F0.5":"41.1"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1607.06153","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}