{"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/part-of-speech-tagging-with-bidirectional","title":"Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network","arxiv_id":"1510.06168","date":"2015-10-21","proceeding":null,"authors":["Peilu Wang","Yao Qian","Frank K. Soong","Lei He","Hai Zhao"],"abstract":"Bidirectional Long Short-Term Memory Recurrent Neural Network (BLSTM-RNN) has\nbeen shown to be very effective for tagging sequential data, e.g. speech\nutterances or handwritten documents. While word embedding has been demoed as a\npowerful representation for characterizing the statistical properties of\nnatural language. In this study, we propose to use BLSTM-RNN with word\nembedding for part-of-speech (POS) tagging task. When tested on Penn Treebank\nWSJ test set, a state-of-the-art performance of 97.40 tagging accuracy is\nachieved. Without using morphological features, this approach can also achieve\na good performance comparable with the Stanford POS tagger.","url_abs":"http://arxiv.org/abs/1510.06168v1","url_pdf":"http://arxiv.org/pdf/1510.06168v1.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":"part-of-speech-tagging-with-bidirectional","repo_url":"https://github.com/Billotais/TDDE09_project","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"part-of-speech-tagging-with-bidirectional","repo_url":"https://github.com/ShashSec/SMTI_SA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"part-of-speech-tagging-with-bidirectional","repo_url":"https://github.com/aneesh-joshi/LSTM_POS_Tagger","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"part-of-speech-tagging-with-bidirectional","repo_url":"https://github.com/harshvivek14/NLP-POS-Tagging-using-Viterbi-Algorithm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"pos","task_name":"POS"},{"task_slug":"pos-tagging","task_name":"POS Tagging"},{"task_slug":"part-of-speech-tagging","task_name":"Part-Of-Speech Tagging"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1510.06168","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}