{"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/free-as-in-free-word-order-an-energy-based","title":"Free as in Free Word Order: An Energy Based Model for Word Segmentation and Morphological Tagging in Sanskrit","arxiv_id":"1809.01446","date":"2018-09-05","proceeding":"EMNLP 2018 10","authors":["Amrith Krishna","Bishal Santra","Sasi Prasanth Bandaru","Gaurav Sahu","Vishnu Dutt Sharma","Pavankumar Satuluri","Pawan Goyal"],"abstract":"The configurational information in sentences of a free word order language\nsuch as Sanskrit is of limited use. Thus, the context of the entire sentence\nwill be desirable even for basic processing tasks such as word segmentation. We\npropose a structured prediction framework that jointly solves the word\nsegmentation and morphological tagging tasks in Sanskrit. We build an energy\nbased model where we adopt approaches generally employed in graph based parsing\ntechniques (McDonald et al., 2005a; Carreras, 2007). Our model outperforms the\nstate of the art with an F-Score of 96.92 (percentage improvement of 7.06%)\nwhile using less than one-tenth of the task-specific training data. We find\nthat the use of a graph based ap- proach instead of a traditional lattice-based\nsequential labelling approach leads to a percentage gain of 12.6% in F-Score\nfor the segmentation task.","url_abs":"http://arxiv.org/abs/1809.01446v2","url_pdf":"http://arxiv.org/pdf/1809.01446v2.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":"free-as-in-free-word-order-an-energy-based","repo_url":"https://github.com/Demfier/ebm-sanskrit-word-segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"morphological-tagging","task_name":"Morphological Tagging"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"structured-prediction","task_name":"Structured Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1809.01446","atlas_url":"https://app.syntology.ai/?focus=1809.01446","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}