AMPS-JuST: Dataset of Annotated Judgements from the Small Claims Tribunal

AMPS-JuST: Dataset of Annotated Judgements from the Small Claims Tribunal | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article AMPS-JuST: Dataset of Annotated Judgements from the Small Claims Tribunal Charlie Abela, Ivan Mifsud, Joel Azzopardi, Kurt Xerri, James Farrugia, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8701542/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract AMPS–JuST is a bilingual (Maltese–English) corpus of 16,670 judgements delivered by the Maltese Small Claims Tribunal. We automatically scraped the originals, applied a domain-specific PDF cleaning and segmentation pipeline, and split each decision into a reasoning and conclusion. Using GPT-4o and open-weight LLM baselines we then (i) generated sentence-level summaries in Maltese and English, (ii) assigned eight rhetorical role labels to every summary sentence, (iii) extracted case verdicts through a hybrid rule-based + LLM procedure, and (iv) tagged each case with a two-level thematic taxonomy. The resulting JSON corpus therefore links raw text, rich meta-data, bilingual summaries, rhetorical structure, thematic labels, and outcome fields in a machine-readable format. Expert review of 30 randomly sampled cases (5000 + sentences) on a five-factor Likert scale confirms high structural coherence (mean 4.7/5), faithful preservation of legal reasoning (4.6/5), and negligible hallucination or bias (≤4% of items). By pairing high-quality English representations with the original Maltese texts, AMPS-JuST lowers the entry barrier for legal NLP in a severely under-resourced language and provides a benchmark for cross-lingual retrieval, classification, summarisation and judgment-prediction research. Legal NLP Low-Resource Languages Bilingual Corpus Rhetorical Role Labelling Summarisation Verdict Extraction Thematic Tagging Maltese Small Claims Tribunal Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8701542","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583395206,"identity":"7b6f1eec-d361-43d6-9f5e-0d099fa83fe2","order_by":0,"name":"Charlie Abela","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYDACCSB+YABmMB5gqACLGRDWkgDRwnCA4QxcCx5tYC1QxgHGNiK08M9ufvYhocAGxDhw4Oe8w9EM7M3bJBhz/uC25M4x4xkJBmkgRsLB3m2Hcxt4jpVJMG7DbYuBRIIx0C+HGRhu5Bgc4AVpkcgxI6Al/TNQy38G+Rv5Hw7+nQPUIv+GkJYckC0HGAxu5DAc5m0A2cKDX4vEjZxioJZkHsM7xwwOyxxLz23jSSu2SNxmjFML/4z0zQwf/tjJyd1ufvjwTY11bj/74Y03Pm6Tw6kFBnjgLDYQkUBQwygYBaNgFIwCfAAAB9RUWWr7cV8AAAAASUVORK5CYII=","orcid":"","institution":"University of Malta","correspondingAuthor":true,"prefix":"","firstName":"Charlie","middleName":"","lastName":"Abela","suffix":""},{"id":583395207,"identity":"fc6ab722-32ec-4747-9021-169c1d5fe5ac","order_by":1,"name":"Ivan Mifsud","email":"","orcid":"","institution":"University of Malta","correspondingAuthor":false,"prefix":"","firstName":"Ivan","middleName":"","lastName":"Mifsud","suffix":""},{"id":583395208,"identity":"0a547862-b736-461d-a6e6-0abc6e8e226f","order_by":2,"name":"Joel Azzopardi","email":"","orcid":"","institution":"University of Malta","correspondingAuthor":false,"prefix":"","firstName":"Joel","middleName":"","lastName":"Azzopardi","suffix":""},{"id":583395209,"identity":"57b79bbb-c4df-47ec-95d9-dc6b7e02da1e","order_by":3,"name":"Kurt Xerri","email":"","orcid":"","institution":"University of Malta","correspondingAuthor":false,"prefix":"","firstName":"Kurt","middleName":"","lastName":"Xerri","suffix":""},{"id":583395210,"identity":"62e1ca09-cfb2-4762-9fc2-1f4dbb3be5d4","order_by":4,"name":"James Farrugia","email":"","orcid":"","institution":"University of Malta","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Farrugia","suffix":""},{"id":583395211,"identity":"a49f2a41-7aec-499f-bcba-340ab3481d45","order_by":5,"name":"Ayrton Azzopardi","email":"","orcid":"","institution":"University of Malta","correspondingAuthor":false,"prefix":"","firstName":"Ayrton","middleName":"","lastName":"Azzopardi","suffix":""}],"badges":[],"createdAt":"2026-01-26 14:54:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8701542/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8701542/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102397984,"identity":"b01b925b-5a02-42fd-a256-bf2042d8d5ab","added_by":"auto","created_at":"2026-02-11 10:20:21","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":956830,"visible":true,"origin":"","legend":"","description":"","filename":"AMPSJuSTDatasetofAnnotatedJudgementsfromtheSmallClaimsTribunal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8701542/v1_covered_302b68bd-a869-410b-b9fa-d0e2372ac50e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"AMPS-JuST: Dataset of Annotated Judgements from the Small Claims Tribunal","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Legal NLP, Low-Resource Languages, Bilingual Corpus, Rhetorical Role Labelling, Summarisation, Verdict Extraction, Thematic Tagging, Maltese, Small Claims Tribunal","lastPublishedDoi":"10.21203/rs.3.rs-8701542/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8701542/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"AMPS–JuST is a bilingual (Maltese–English) corpus of 16,670 judgements delivered by the Maltese Small Claims Tribunal. 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