{"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/recurrent-neural-network-based-part-of-speech","title":"Recurrent Neural Network based Part-of-Speech Tagger for Code-Mixed Social Media Text","arxiv_id":"1611.04989","date":"2016-11-15","proceeding":null,"authors":["Raj Nath Patel","Prakash B. Pimpale","M Sasikumar"],"abstract":"This paper describes Centre for Development of Advanced Computing's (CDACM)\nsubmission to the shared task-'Tool Contest on POS tagging for Code-Mixed\nIndian Social Media (Facebook, Twitter, and Whatsapp) Text', collocated with\nICON-2016. The shared task was to predict Part of Speech (POS) tag at word\nlevel for a given text. The code-mixed text is generated mostly on social media\nby multilingual users. The presence of the multilingual words,\ntransliterations, and spelling variations make such content linguistically\ncomplex. In this paper, we propose an approach to POS tag code-mixed social\nmedia text using Recurrent Neural Network Language Model (RNN-LM) architecture.\nWe submitted the results for Hindi-English (hi-en), Bengali-English (bn-en),\nand Telugu-English (te-en) code-mixed data.","url_abs":"http://arxiv.org/abs/1611.04989v2","url_pdf":"http://arxiv.org/pdf/1611.04989v2.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":"recurrent-neural-network-based-part-of-speech","repo_url":"https://github.com/patelrajnath/dl4nlp-py","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"recurrent-neural-network-based-part-of-speech","repo_url":"https://github.com/patelrajnath/rnn4nlp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"pos","task_name":"POS"},{"task_slug":"pos-tagging","task_name":"POS Tagging"},{"task_slug":"tag","task_name":"TAG"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1611.04989","atlas_url":"https://app.syntology.ai/?focus=1611.04989","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}