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We propose a transfer method that employs information" /> <meta name="twitter:image" content="http://a.academia-assets.com/images/twitter-card.jpeg" /> <meta property="fb:app_id" content="2369844204" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://www.academia.edu/118332111/Transferring_Semantic_Roles_Using_Translation_and_Syntactic_Information" /> <meta property="og:title" content="Transferring Semantic Roles Using Translation and Syntactic Information" /> <meta property="og:image" content="http://a.academia-assets.com/images/open-graph-icons/fb-paper.gif" /> <meta property="og:description" content="Our paper addresses the problem of annotation projection for semantic role labeling for resource-poor languages using supervised annotations from a resource-rich language through parallel data. 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We propose a transfer method that employs information from source and target syntactic dependencies as well as word alignment density to improve the quality of an iterative bootstrapping method. Our experiments yield a 3.5 absolute labeled F-score improvement over a standard annotation projection method.","author":[{"@context":"https://schema.org","@type":"Person","name":"Mona Diab","url":"https://gwu.academia.edu/MDiab"}],"contributor":[],"dateCreated":"2024-04-30","dateModified":"2025-01-31","datePublished":"2017-01-01","headline":"Transferring Semantic Roles Using Translation and Syntactic Information","image":"https://attachments.academia-assets.com/113984329/thumbnails/1.jpg","inLanguage":"en","keywords":["Computer Science","Artificial Intelligence","Natural Language Processing","Machine Translation","Annotation","Bootstrapping 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= {"work":{"id":118332111,"created_at":"2024-04-30T07:31:04.589-07:00","from_world_paper_id":253689091,"updated_at":"2025-01-31T13:06:20.251-08:00","_data":{"abstract":"Our paper addresses the problem of annotation projection for semantic role labeling for resource-poor languages using supervised annotations from a resource-rich language through parallel data. We propose a transfer method that employs information from source and target syntactic dependencies as well as word alignment density to improve the quality of an iterative bootstrapping method. Our experiments yield a 3.5 absolute labeled F-score improvement over a standard annotation projection method.","publisher":"IJCNLP","ai_title_tag":"Improving Semantic Role Labeling Transfer","publication_date":"2017,,"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Transferring Semantic Roles Using Translation and Syntactic Information","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [32411980]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loginModal = {}; window.loginModal.appleClientId = 'edu.academia.applesignon'; window.userInChina = "false";</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":113984329,"attachmentType":"pdf"}"><img alt="First page of “Transferring Semantic Roles Using Translation and Syntactic Information”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/113984329/mini_magick20240802-1-qa2mz8.png?1722607904" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/images/single_work_splash/adobe_icon.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Transferring Semantic Roles Using Translation and Syntactic Information</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="32411980" href="https://gwu.academia.edu/MDiab"><img alt="Profile image of Mona Diab" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Mona Diab</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2017</p><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">7 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 118332111; const worksViewsPath = "/v0/works/views?subdomain_param=api&work_ids%5B%5D=118332111"; const getWorkViews = async (workId) => { const response = await fetch(worksViewsPath); if (!response.ok) { throw new Error('Failed to load work views'); } const data = await response.json(); return data.views[workId]; }; // Get the view count for the work - we send this immediately rather than waiting for // the DOM to load, so it can be available as soon as possible (but without holding up // the backend or other resource requests, because it's a bit expensive and not critical). const viewCount = await getWorkViews(workId); const updateViewCount = (viewCount) => { try { const viewCountNumber = parseInt(viewCount, 10); if (viewCountNumber === 0) { // Remove the whole views element if there are zero views. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); return; } const commaizedViewCount = viewCountNumber.toLocaleString(); const viewCountBody = document.getElementById('work-metadata-view-count'); if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">Our paper addresses the problem of annotation projection for semantic role labeling for resource-poor languages using supervised annotations from a resource-rich language through parallel data. We propose a transfer method that employs information from source and target syntactic dependencies as well as word alignment density to improve the quality of an iterative bootstrapping method. Our experiments yield a 3.5 absolute labeled F-score improvement over a standard annotation projection method.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":113984329,"attachmentType":"pdf","workUrl":"https://www.academia.edu/118332111/Transferring_Semantic_Roles_Using_Translation_and_Syntactic_Information"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":113984329,"attachmentType":"pdf","workUrl":"https://www.academia.edu/118332111/Transferring_Semantic_Roles_Using_Translation_and_Syntactic_Information"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div><div class="ds-signup-banner-trigger-container"><div class="ds-signup-banner-trigger ds-signup-banner-trigger-control"></div></div><div class="ds-signup-banner ds-signup-banner-control"><div id="ds-signup-banner-close-button"><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--inverse"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">close</span></button></div><div class="ds-signup-banner-ctas"><img src="//a.academia-assets.com/images/academia-logo-capital-white.svg" /><h4 class="ds2-5-heading-serif-sm">Sign up for access to the world's latest research</h4><button class="ds2-5-button ds2-5-button--inverse ds2-5-button--full-width js-swp-download-button" data-signup-modal="{"location":"signup-banner"}">Sign up for free<span class="material-symbols-outlined" style="font-size: 20px" translate="no">arrow_forward</span></button></div><div class="ds-signup-banner-divider"></div><div class="ds-signup-banner-reasons"><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Get notified about relevant papers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Save papers to use in your research</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Join the discussion with peers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Track your impact</span></div></div></div><script>(() => { // Set up signup banner show/hide behavior: // 1. 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We propose a general framework that is based on annotation projection, phrased as a graph optimization problem. It is relatively inexpensive and has the potential to reduce the human effort involved in creating role-semantic resources. Within this framework, we present projection models that exploit lexical and syntactic information. We provide an experimental evaluation on an English-German parallel corpus which demonstrates the feasibility of inducing high-precision German semantic role annotation both for manually and automatically annotated English data.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Cross-lingual Annotation Projection of Semantic Roles","attachmentId":55013485,"attachmentType":"pdf","work_url":"https://www.academia.edu/35151642/Cross_lingual_Annotation_Projection_of_Semantic_Roles","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/35151642/Cross_lingual_Annotation_Projection_of_Semantic_Roles"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="14976636" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/14976636/Scaling_up_automatic_cross_lingual_semantic_role_annotation">Scaling up automatic cross-lingual semantic role annotation</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="33971246" href="https://independent.academia.edu/JamesHenderson28">James Henderson</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2011</p><p class="ds-related-work--abstract ds2-5-body-sm">Broad-coverage semantic annotations for training statistical learners are only available for a handful of languages. Previous approaches to cross-lingual transfer of semantic annotations have addressed this problem with encouraging results on a small scale. In this paper, we scale up previous efforts by using an automatic approach to semantic annotation that does not rely on a semantic ontology for the target language. Moreover, we improve the quality of the transferred semantic annotations by using a joint syntacticsemantic parser that learns the correlations between syntax and semantics of the target language and smooths out the errors from automatic transfer. We reach a labelled F-measure for predicates and arguments of only 4% and 9% points, respectively, lower than the upper bound from manual annotations.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Scaling up automatic cross-lingual semantic role annotation","attachmentId":43681495,"attachmentType":"pdf","work_url":"https://www.academia.edu/14976636/Scaling_up_automatic_cross_lingual_semantic_role_annotation","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/14976636/Scaling_up_automatic_cross_lingual_semantic_role_annotation"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="60127357" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/60127357/Cross_lingual_Annotation_Projection_for_Semantic_Roles">Cross-lingual Annotation Projection for Semantic Roles</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="78456069" href="https://independent.academia.edu/SebastianPado">Sebastian Padó</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Artificial Intelligence Research, 2009</p><p class="ds-related-work--abstract ds2-5-body-sm">This article considers the task of automatically inducing role-semantic annotations in the FrameNet paradigm for new languages. We propose a general framework that is based on annotation projection, phrased as a graph optimization problem. It is relatively inex- pensive and has the potential to reduce the human eort involved in creating role-semantic resources. Within this framework, we present projection models</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Cross-lingual Annotation Projection for Semantic Roles","attachmentId":73704906,"attachmentType":"pdf","work_url":"https://www.academia.edu/60127357/Cross_lingual_Annotation_Projection_for_Semantic_Roles","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/60127357/Cross_lingual_Annotation_Projection_for_Semantic_Roles"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="86233183" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/86233183/Cross_Lingual_Transfer_of_Semantic_Roles_From_Raw_Text_to_Semantic_Roles">Cross-Lingual Transfer of Semantic Roles: From Raw Text to Semantic Roles</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32411980" href="https://gwu.academia.edu/MDiab">Mona Diab</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Proceedings of the 13th International Conference on Computational Semantics - Long Papers, 2019</p><p class="ds-related-work--abstract ds2-5-body-sm">We describe a transfer method based on annotation projection to develop a dependency-based semantic role labeling system for languages for which no supervised linguistic information other than parallel data is available. Unlike previous work that presumes the availability of supervised features such as lemmas, part-of-speech tags, and dependency parse trees, we only make use of word and character features. Our deep model considers using character-based representations as well as unsupervised stem embeddings to alleviate the need for supervised features. Our experiments outperform a state-of-the-art method that uses supervised lexico-syntactic features on 6 out of 7 languages in the Universal Proposition Bank.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Cross-Lingual Transfer of Semantic Roles: From Raw Text to Semantic Roles","attachmentId":90733427,"attachmentType":"pdf","work_url":"https://www.academia.edu/86233183/Cross_Lingual_Transfer_of_Semantic_Roles_From_Raw_Text_to_Semantic_Roles","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/86233183/Cross_Lingual_Transfer_of_Semantic_Roles_From_Raw_Text_to_Semantic_Roles"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="104213943" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/104213943/Global_Methods_for_Cross_lingual_Semantic_Role_and_Predicate_Labelling">Global Methods for Cross-lingual Semantic Role and Predicate Labelling</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="115928881" href="https://malta.academia.edu/LonnekevanderPlas">Lonneke van der Plas</a></div><p class="ds-related-work--abstract ds2-5-body-sm">We address the problem of transferring semantic annotations to new languages using parallel corpora. Previous work has transferred these annotations on a token-to-token basis, an approach that is sensitive to alignment errors and translation shifts. We present a global approach to transfer that aggregates information across the whole parallel corpus and leads to more robust labellers. We build two global models, one for predicate labelling and one for role labelling, each tailored to the task at hand. We show that the combination of direct and global methods outperforms previous results.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Global Methods for Cross-lingual Semantic Role and Predicate Labelling","attachmentId":104002593,"attachmentType":"pdf","work_url":"https://www.academia.edu/104213943/Global_Methods_for_Cross_lingual_Semantic_Role_and_Predicate_Labelling","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/104213943/Global_Methods_for_Cross_lingual_Semantic_Role_and_Predicate_Labelling"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="61528971" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/61528971/Exploring_multilingual_semantic_role_labeling">Exploring multilingual semantic role labeling</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="33330217" href="https://independent.academia.edu/MartinEmms">Martin Emms</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Proceedings of the Thirteenth Conference on Computational Natural Language Learning Shared Task - CoNLL '09, 2009</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper describes the multilingual semantic role labeling system of Computational Linguistics Group, Trinity College Dublin, for the CoNLL-2009 SRLonly closed shared task. The system consists of two cascaded components: one for disambiguating predicate word sense, and the other for identifying and classifying arguments. Supervised learning techniques are utilized in these two components. As each language has its unique characteristics, different parameters and strategies have to be taken for different languages, either for providing functions required by a language or for meeting the tight deadline. The system obtained labeled F1 69.26 averaging over seven languages (Catalan, Chinese, Czech, English, German, Japanese, and Spanish), which ranks the system fourth among the seven systems participating the SRLonly closed track.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Exploring multilingual semantic role labeling","attachmentId":74535304,"attachmentType":"pdf","work_url":"https://www.academia.edu/61528971/Exploring_multilingual_semantic_role_labeling","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/61528971/Exploring_multilingual_semantic_role_labeling"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="14976640" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/14976640/D6_2_Semantic_Role_Annotation_of_a_French_English_Corpus">D6. 2: Semantic Role Annotation of a French-English Corpus</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="33971246" href="https://independent.academia.edu/JamesHenderson28">James Henderson</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="24919989" href="https://unige.academia.edu/paolamerlo">paola merlo</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2010</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"D6. 2: Semantic Role Annotation of a French-English Corpus","attachmentId":43681504,"attachmentType":"pdf","work_url":"https://www.academia.edu/14976640/D6_2_Semantic_Role_Annotation_of_a_French_English_Corpus","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/14976640/D6_2_Semantic_Role_Annotation_of_a_French_English_Corpus"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="3097762" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/3097762/Towards_automatic_cross_lingual_transfer_of_semantic_annotation">Towards automatic cross-lingual transfer of semantic annotation</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="3359108" href="https://uaic.academia.edu/DianaTrandabat">Diana Trandabat</a></div><p class="ds-related-work--abstract ds2-5-body-sm">In order to develop a semantic labeling system, the most common methods use supervised learning from an annotated corpus. What if we have short deadlines and limited human and financial possibilities that prevent us from building such a training corpus for our language? If such a corpus already exists for any other language, this paper proposes a method to automatically import the existing corpus for the language we need. The transfer method is based on translating the existing corpus (or using annotated versions of existing parallel texts), aligning it at word level, and applying a set of mapping functions to import the annotation from one language to another. An import validation interface is also offered for the manual validation of the resulted resource. As an example, the case of semantic role import from the English FrameNet to Romanian is discussed. RÉSUMÉ. Afin de développer un système d'étiquetage sémantique automatique, les méthodes les plus fréquentes utilisent l'apprentissage supervisé à partir d'un corpus annoté. Et si on a des délais courts et des possibilités humaines et financières limitées, qui nous empêchent de construire un tel corpus d'apprentissage pour la langue de notre choix? Si un tel corpus existe déjà pour une autre langue, cet article propose une méthode pour importer automatiquement le corpus existant dans la langue où nous le nécessitons. La méthode de transfert présentée dans cet article est basée sur la traduction du corpus existant (ou l'utilisation d'une version parallèle annotée du texte), l'alignement au niveau du mot des deux versions de texte, et l'application d'un set de fonctions de mappage pour importer l'annotation d'une langue à l'autre. Une interface de validation de l'import est également offerte pour la validation manuelle de la ressource obtenue. A titre d'exemple, le cas de l'import des rôles sémantiques de la ressource anglaise FrameNet vers le roumain est discuté.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Towards automatic cross-lingual transfer of semantic annotation","attachmentId":31026763,"attachmentType":"pdf","work_url":"https://www.academia.edu/3097762/Towards_automatic_cross_lingual_transfer_of_semantic_annotation","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/3097762/Towards_automatic_cross_lingual_transfer_of_semantic_annotation"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="60127462" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/60127462/Cross_linguistic_projection_of_role_semantic_information">Cross-linguistic projection of role-semantic information</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="78456069" href="https://independent.academia.edu/SebastianPado">Sebastian Padó</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05, 2005</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper considers the problem of automatically inducing role-semantic annotations in the FrameNet paradigm for new languages. We introduce a general framework for semantic projection which exploits parallel texts, is relatively inexpensive and can potentially reduce the amount of effort involved in creating semantic resources. We propose projection models that exploit lexical and syntactic information. Experimental results on an English-German parallel corpus demonstrate the advantages of this approach.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Cross-linguistic projection of role-semantic information","attachmentId":73704980,"attachmentType":"pdf","work_url":"https://www.academia.edu/60127462/Cross_linguistic_projection_of_role_semantic_information","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/60127462/Cross_linguistic_projection_of_role_semantic_information"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="1951603" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/1951603/Using_cross_lingual_projections_to_generate_semantic_role_labeled_corpus_for_Urdu_a_resource_poor_language">Using cross-lingual projections to generate semantic role labeled corpus for Urdu: a resource poor language</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="2537548" href="https://rutgers.academia.edu/DebanjanGhosh">Debanjan Ghosh</a></div><p class="ds-related-work--metadata ds2-5-body-xs">… of the 23rd International Conference on …, 2010</p><p class="ds-related-work--abstract ds2-5-body-sm">In this paper we explore the possibility of using cross lingual projections that help to automatically induce role-semantic annotations in the PropBank paradigm for Urdu, a resource poor language. This technique provides annotation projections based on word alignments. It is relatively inexpensive and has the potential to reduce human effort involved in creating semantic role resources. The projection model exploits lexical as well as syntactic information on an English-Urdu parallel corpus. We show that our method generates reasonably good annotations with an accuracy of 92% on short structured sentences. Using the automatically generated annotated corpus, we conduct preliminary experiments to create a semantic role labeler for Urdu. The results of the labeler though modest, are promising and indicate the potential of our technique to generate large scale annotations for Urdu.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Using cross-lingual projections to generate semantic role labeled corpus for Urdu: a resource poor language","attachmentId":28209800,"attachmentType":"pdf","work_url":"https://www.academia.edu/1951603/Using_cross_lingual_projections_to_generate_semantic_role_labeled_corpus_for_Urdu_a_resource_poor_language","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/1951603/Using_cross_lingual_projections_to_generate_semantic_role_labeled_corpus_for_Urdu_a_resource_poor_language"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":113984329,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":113984329,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_113984329" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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