{"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/nlp-cube-end-to-end-raw-text-processing-with","title":"NLP-Cube: End-to-End Raw Text Processing With Neural Networks","arxiv_id":null,"date":"2018-10-01","proceeding":"CONLL 2018 10","authors":["Tiberiu Boros","Stefan Daniel Dumitrescu","Rux Burtica","ra"],"abstract":"We introduce NLP-Cube: an end-to-end Natural Language Processing framework, evaluated in CoNLL{'}s {``}Multilingual Parsing from Raw Text to Universal Dependencies 2018{''} Shared Task. It performs sentence splitting, tokenization, compound word expansion, lemmatization, tagging and parsing. Based entirely on recurrent neural networks, written in Python, this ready-to-use open source system is freely available on GitHub. For each task we describe and discuss its specific network architecture, closing with an overview on the results obtained in the competition.","url_abs":"https://aclanthology.org/K18-2017","url_pdf":"https://aclanthology.org/K18-2017.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":"nlp-cube-end-to-end-raw-text-processing-with","repo_url":"https://github.com/adobe/NLP-Cube","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"lemmatization","task_name":"Lemmatization"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}