{"id":276898,"date":"2023-07-31T18:14:25","date_gmt":"2023-07-31T16:14:25","guid":{"rendered":"https:\/\/daily.jusconnect.com\/?p=276898"},"modified":"2023-08-22T14:23:48","modified_gmt":"2023-08-22T12:23:48","slug":"jus-mundis-data-science-team-won-4th-place-at-semeval-2023","status":"publish","type":"post","link":"https:\/\/dailyjus.com\/index.php\/2023\/07\/31\/jus-mundis-data-science-team-won-4th-place-at-semeval-2023\/","title":{"rendered":"Jus Mundi\u2019s Data Science Team Won 4th Place at SemEval 2023\u00a0"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">This year, <a href=\"https:\/\/jusmundi.com\/en\" target=\"_blank\" rel=\"noreferrer noopener\">Jus Mundi<\/a>\u2019s data science team decided to participate at SemEval 2023 <a id=\"_ftnref1\" href=\"#_ftn1\">[1]<\/a>, more specifically on Task 6 \u2013 B, \u201cLegalEval: Understanding Legal Texts Legal Named Entity Recognition\u201d. The goal of this task was to create a Named Entity Recognition system capable of detecting 14 types of legal named entities, such as Claimant, Judge, Witness, and Organizations, in Indian judgments.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>What is Legal Named Entity Recognition?<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Named Entity recognition, also known as NER, is a Natural Language Processing (NLP) task, that relies on tagging a word, or a group of them, with semantic labels, such as Location, Person, and Organization <a id=\"_ftnref2\" href=\"#_ftn2\">[2]<\/a>. In the case of Legal NER, these entities can be those related to the parties, such as Claimant and Respondent, but also those more related to judgments, such as Judge, Lawyer, Witness, Provisions, and Statutes.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"602\" height=\"386\" src=\"https:\/\/daily.jusconnect.com\/wp-content\/uploads\/2023\/08\/word-image-277001-1.jpeg\" alt=\"\" class=\"wp-image-277003\" srcset=\"https:\/\/daily.jusconnect.com\/~www\/wp-content\/uploads\/2023\/08\/word-image-277001-1.jpeg 602w, https:\/\/daily.jusconnect.com\/~www\/wp-content\/uploads\/2023\/08\/word-image-277001-1-300x192.jpeg 300w\" sizes=\"(max-width: 602px) 100vw, 602px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"has-text-align-center has-small-font-size wp-block-paragraph\">Figure 1: Examples of annotations for Legal Named Entity Recognition<\/p>\n\n\n\n<div style=\"height:14px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>About Jus Mundi\u2019s Participation<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Jus Mundi decided to participate in Task 6 &#8211; B using technologies that our team of Data Scientists has developed in-house to deal with similar problems within Jus Mundi data. Specifically, we built a Legal NER using machine learning, using an architecture called Frustratingly Easy Domain Adaptation <a id=\"_ftnref3\" href=\"#_ftn3\">[3]<\/a> <a id=\"_ftnref4\" href=\"#_ftn4\">[4]<\/a>. The goal of this architecture is to train a model where the knowledge between different collections of data is shared in order to create a robust NER system. We created this architecture using PyTorch, a well-known framework to create neural networks, and DeBERTa-V3, a language model trained by Microsoft and accessible through the HuggingFace platform. Moreover, Jus Mundi trained this model using the French super-calculator \u201cJean Zay\u201d, through our project allocation <em>2022-AD011012667R1<\/em>.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"805\" height=\"356\" src=\"https:\/\/daily.jusconnect.com\/wp-content\/uploads\/2023\/08\/word-image-277001-2.jpeg\" alt=\"\" class=\"wp-image-277004\" srcset=\"https:\/\/daily.jusconnect.com\/~www\/wp-content\/uploads\/2023\/08\/word-image-277001-2.jpeg 805w, https:\/\/daily.jusconnect.com\/~www\/wp-content\/uploads\/2023\/08\/word-image-277001-2-300x133.jpeg 300w, https:\/\/daily.jusconnect.com\/~www\/wp-content\/uploads\/2023\/08\/word-image-277001-2-768x340.jpeg 768w, https:\/\/daily.jusconnect.com\/~www\/wp-content\/uploads\/2023\/08\/word-image-277001-2-750x332.jpeg 750w\" sizes=\"(max-width: 805px) 100vw, 805px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"has-text-align-center has-small-font-size wp-block-paragraph\">Figure 2: Simplified architecture of Jus Mundi\u2019s participation at SemEval 2023.<\/p>\n\n\n\n<p class=\"has-text-align-center has-small-font-size wp-block-paragraph\">The image of Jean Zay comes from <a id=\"_ftnref5\" href=\"#_ftn5\">[5]<\/a><\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">Our team of Data Scientists reached the 4<sup>th <\/sup>place, out of of 17 participants from all around the world, with a score of 0.9007 out of 1.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If you want to know more about Jus Mundi\u2019s participation, read our full article <strong>&nbsp;<\/strong><a href=\"https:\/\/aclanthology.org\/2023.semeval-1.247\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>here<\/strong><\/a>.<\/p>\n\n\n\n<div style=\"height:14px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Bio<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Luis Adri\u00e1n Cabrera-Diego<\/strong> is a Data Scientist at <a href=\"https:\/\/jusmundi.com\/en\/about\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Jus Mundi<\/strong><\/a>. He has a Ph.D. in Computer Science from the University of Avignon and he is a Computer Engineer from the National Autonomous University of Mexico (UNAM). Before joining Jus Mundi, he worked on two European Projects Horizon 2020 as a postdoctorate, at Edge Hill University, U.K., and at the University of La Rochelle, France.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"#_ftnref1\" id=\"_ftn1\">[1]<\/a> SemEval is a series of research workshops that focus on natural language processing tasks. https:\/\/semeval.github.io\/<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"#_ftnref2\" id=\"_ftn2\">[2]<\/a> Li J, Sun A, Han J, Li C. A Survey on Deep Learning for Named Entity Recognition. IEEE Transactions on Knowledge and Data Engineering. 2020:1-1.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a id=\"_ftn3\" href=\"#_ftnref3\">[3]<\/a> Daum\u00b4e III H. Frustratingly Easy Domain Adaptation. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic: Association for Computational Linguistics; 2007. p. 256-63. Available from: <a href=\"https:\/\/www.aclweb.org\/anthology\/P07-1033\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/www.aclweb.org\/anthology\/P07-1033<\/a><a href=\"https:\/\/www.aclweb.org\/anthology\/P07-1033\">.<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"#_ftnref4\" id=\"_ftn4\">[4]<\/a> Cabrera-Diego LA, Moreno JG, Doucet A. Using a Frustratingly Easy Domain and Tagset Adaptation for Creating Slavic Named Entity Recognition Systems. In: Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing. Kiyv, Ukraine: Association for Computational Linguistics; 2021. p. 98-104. Available from: https:\/\/www.aclweb.org\/ anthology\/2021.bsnlp-1.12.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"#_ftnref5\" id=\"_ftn5\">[5]<\/a> Com-idris. Le supercalculateur Jean Zay de l\u2019IDRIS; 2020. [Online; accessed July 24, 2023]. Available from: https:\/\/commons.wikimedia.org\/wiki\/ File:Le_supercalculateur_Jean_Zay_.jpg.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This year, Jus Mundi\u2019s data science team decided to participate at SemEval 2023. Our team reached the 4th place, out of of 17 participants from all around the world.<\/p>\n","protected":false},"author":3,"featured_media":276906,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jnews-multi-image_gallery":[],"jnews_single_post":{"subtitle":"","format":"standard","video":"","gallery":"","source_name":"","source_url":"","via_name":"","via_url":"","override_template":"0","override":[{"template":"custom","single_blog_custom":"274736","parallax":"1","fullscreen":"1","layout":"right-sidebar","sidebar":"author","second_sidebar":"default-sidebar","sticky_sidebar":"1","share_position":"hide","share_float_style":"share-monocrhome","show_share_counter":"0","show_view_counter":"0","show_featured":"1","show_post_meta":"1","show_post_author":"0","show_post_author_image":"0","show_post_date":"1","post_date_format":"default","post_date_format_custom":"Y\/m\/d","show_post_category":"0","show_post_reading_time":"0","post_reading_time_wpm":"300","show_zoom_button":"0","zoom_button_out_step":"2","zoom_button_in_step":"3","show_post_tag":"0","show_prev_next_post":"0","show_popup_post":"0","number_popup_post":"1","show_author_box":"0","show_post_related":"0","show_inline_post_related":"0"}],"override_image_size":"0","image_override":[{"single_post_thumbnail_size":"crop-500","single_post_gallery_size":"crop-500"}],"trending_post":"0","trending_post_position":"meta","trending_post_label":"Trending","sponsored_post":"0","sponsored_post_label":"Sponsored by","sponsored_post_name":"","sponsored_post_url":"","sponsored_post_logo_enable":"0","sponsored_post_logo":"","sponsored_post_desc":"","disable_ad":"0"},"jnews_primary_category":{"id":"146","hide":""},"jnews_social_meta":{"fb_title":"Jus Mundi\u2019s Data Science Team Won 4th Place at SemEval 2023","fb_description":"This year, Jus Mundi\u2019s data science team decided to participate at SemEval 2023. 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