{"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/italy-goes-to-stanford-a-collection-of","title":"Italy goes to Stanford: a collection of CoreNLP modules for Italian","arxiv_id":"1609.06204","date":"2016-09-20","proceeding":null,"authors":["Alessio Palmero Aprosio","Giovanni Moretti"],"abstract":"In this we paper present Tint, an easy-to-use set of fast, accurate and\nextendable Natural Language Processing modules for Italian. It is based on\nStanford CoreNLP and is freely available as a standalone software or a library\nthat can be integrated in an existing project.","url_abs":"http://arxiv.org/abs/1609.06204v2","url_pdf":"http://arxiv.org/pdf/1609.06204v2.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":"italy-goes-to-stanford-a-collection-of","repo_url":"https://github.com/musixmatchresearch/umberto","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"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}