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WN18RR Dataset | Papers With Code
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WN18 consists of 18 relations and 40,943 entities. However, many text triples are obtained by inverting triples from the training set. Thus the WN18RR dataset is created to ensure that the evaluation dataset does not have inverse relation test leakage. In summary, WN18RR dataset contains 93,003 triples with 40,943 entities and 11 relation types." /> <!-- Open Graph protocol metadata --> <meta property="og:title" content="Papers with Code - WN18RR Dataset"> <meta property="og:description" content="WN18RR is a link prediction dataset created from WN18, which is a subset of WordNet. WN18 consists of 18 relations and 40,943 entities. However, many text triples are obtained by inverting triples from the training set. Thus the WN18RR dataset is created to ensure that the evaluation dataset does not have inverse relation test leakage. In summary, WN18RR dataset contains 93,003 triples with 40,943 entities and 11 relation types."> <meta property="og:image" content="https://production-media.paperswithcode.com/datasets/default.gif"> <meta property="og:url" content="https://paperswithcode.com/dataset/wn18rr"> <!-- Twitter metadata --> <meta name="twitter:card" content="summary_large_image"> <meta name="twitter:site" content="@paperswithcode"> <meta name="twitter:title" content="Papers with Code - WN18RR Dataset"> <meta name="twitter:description" content="WN18RR is a link prediction dataset created from WN18, which is a subset of WordNet. WN18 consists of 18 relations and 40,943 entities. However, many text triples are obtained by inverting triples from the training set. Thus the WN18RR dataset is created to ensure that the evaluation dataset does not have inverse relation test leakage. In summary, WN18RR dataset contains 93,003 triples with 40,943 entities and 11 relation types."> <meta name="twitter:creator" content="@paperswithcode"> <meta name="twitter:url" content="https://paperswithcode.com/dataset/wn18rr"> <meta name="twitter:domain" content="paperswithcode.com"> <!-- JSON LD --> <script type="application/ld+json">{ "@context": "http://schema.org", "@graph": { "@type": "Dataset", "@id": "wn18rr", "name": "WN18RR Dataset", "description": "WN18RR is a link prediction dataset created from WN18, which is a subset of WordNet. WN18 consists of 18 relations and 40,943 entities. However, many text triples are obtained by inverting triples from the training set. Thus the WN18RR dataset is created to ensure that the evaluation dataset does not have inverse relation test leakage. In summary, WN18RR dataset contains 93,003 triples with 40,943 entities and 11 relation types.", "url": "https://paperswithcode.com/dataset/wn18rr", "image": "https://production-media.paperswithcode.com/datasets/default.gif", "headline": "WN18RR Dataset", "author": [ { "@type": "Person", "@id": "#Antoine_Bordes", "name": "Antoine Bordes", "image": "https://paperswithcode.com/static/" }, { "@type": "Person", "@id": "#Nicolas_Usunier", "name": "Nicolas Usunier", "image": "https://paperswithcode.com/static/" }, { "@type": "Person", "@id": "#Alberto_Garcia-Duran", "name": "Alberto Garcia-Duran", "image": "https://paperswithcode.com/static/" }, { "@type": "Person", "@id": "#Jason_Weston", "name": "Jason Weston", "image": "https://paperswithcode.com/static/" }, { "@type": "Person", "@id": "#Oksana_Yakhnenko", "name": "Oksana Yakhnenko", "image": "https://paperswithcode.com/static/" } ], "includedInDataCatalog": { "@type": "DataCatalog", "name": "Papers with Code", "url": 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class="asteriskField">*</span> </label> <div class=""> <input type="text" name="name" value="WN18RR" class="textinput textInput form-control" required id="id_name"> </div> </div> <div id="div_id_full_name" class="form-group"> <label for="id_full_name" class=""> Full name (optional): </label> <div class=""> <input type="text" name="full_name" class="textinput textInput form-control" id="id_full_name"> </div> </div> <div id="div_id_description" class="form-group"> <label for="id_description" class=" requiredField"> Description (Markdown and $\LaTeX$ enabled):<span class="asteriskField">*</span> </label> <div class=""> <textarea name="description" cols="40" rows="6" placeholder="Briefly describe the dataset. Provide: * a high-level explanation of the dataset characteristics * explain motivations and summary of its content * potential use cases of the dataset If the description or image is from a different paper, please refer to it as follows: Source: [title](url) Image Source: [title](url) " class="md-sources-autocomplete textarea form-control" required id="id_description"> **WN18RR** is a link prediction dataset created from WN18, which is a subset of WordNet. WN18 consists of 18 relations and 40,943 entities. However, many text triples are obtained by inverting triples from the training set. Thus the WN18RR dataset is created to ensure that the evaluation dataset does not have inverse relation test leakage. In summary, WN18RR dataset contains 93,003 triples with 40,943 entities and 11 relation types. Source: [End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion](https://arxiv.org/abs/1811.04441)</textarea> </div> </div> <div id="div_id_url" class="form-group"> <label for="id_url" class=""> Homepage URL (optional): </label> <div class=""> <input type="text" name="url" value="https://download.microsoft.com/download/8/7/0/8700516A-AB3D-4850-B4BB-805C515AECE1/FB15K-237.2.zip" class="textinput textInput form-control" id="id_url"> </div> </div> <div id="div_id_paper" class="form-group"> <label for="id_paper" class=""> Paper where the dataset was introduced: </label> <div class=""> <select name="paper" style="width: 350px" class="modelselect2 form-control custom-select" id="id_paper" data-autocomplete-light-language="en" data-autocomplete-light-url="/sota/autocomplete/paper" data-autocomplete-light-function="select2"> <option value="">---------</option> <option value="79410" selected>Translating Embeddings for Modeling Multi-relational Data</option> 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aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <form action="" method="post"> <input type="hidden" name="csrfmiddlewaretoken" value="QtRro6mANStgKKtBm6mREkq0AnvfMp0E7CgRJDNJvHoESuzZeQ1X3hoXsmFx0LZF"> <div id="div_id_variants" class="form-group"> <label for="id_variants" class=""> Add or remove variants: </label> <div class=""> <select name="variants" data-container-css-class="" data-allow-clear="false" style="width: 100%" class="modelselect2multiple form-control" id="id_variants" data-autocomplete-light-language="en" data-autocomplete-light-url="/dataset-autocomplete/" data-autocomplete-light-function="select2" multiple> <option value="745" selected>WN18RR</option> </select><div style="display:none" class="dal-forward-conf" id="dal-forward-conf-for_id_variants"><script type="text/dal-forward-conf">[{"type": "const", "val": true, "dst": "disable_create_option"}]</script></div> </div> </div> <p> The benchmarks section lists all benchmarks using a given dataset or any of its variants. We use variants to distinguish between results evaluated on slightly different versions of the same dataset. For example, ImageNet 32⨉32 and ImageNet 64⨉64 are variants of the ImageNet dataset. </p> <div class="modal-footer"> <button type="submit" class="btn btn-primary" name="edit-variants"> Save </button> </div> </form> </div> </div> </div> </div> <!-- Add Row --> <div class="modal fade" id="addRow" role="dialog" aria-labelledby="addRowLabel" aria-hidden="true"> <div class="modal-dialog" role="document"> <div class="modal-content"> <div class="modal-header"> <h5 class="modal-title" id="addRowLabel">Add a new evaluation result row</h5> <button type="button" class="close btn-close" data-bs-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <form action="" method="post"> <div class="modal-body"> <input type="hidden" name="csrfmiddlewaretoken" value="QtRro6mANStgKKtBm6mREkq0AnvfMp0E7CgRJDNJvHoESuzZeQ1X3hoXsmFx0LZF"> <div id="div_id_paper" class="form-group"> <label for="id_paper_add_row" class=" requiredField"> Paper title:<span class="asteriskField">*</span> </label> <div class=""> <select name="paper" id="id_paper_add_row" class="modelselect2 form-control" required data-autocomplete-light-language="en" data-autocomplete-light-url="/paper-autocomplete/" data-autocomplete-light-function="select2"> <option value="" selected>---------</option> </select> </div> </div> <div id="div_id_dataset" class="form-group"> <label for="id_dataset" class=" requiredField"> Dataset or its variant:<span class="asteriskField">*</span> </label> <div class=""> <select name="dataset" class="modelselect2 form-control" required id="id_dataset" data-autocomplete-light-language="en" data-autocomplete-light-url="/dataset-autocomplete/" data-autocomplete-light-function="select2"> <option value="">---------</option> <option value="745" selected>WN18RR</option> </select> </div> </div> <div id="div_id_task" class="form-group"> <label for="id_task" class=" requiredField"> Task:<span class="asteriskField">*</span> </label> <div class=""> <select name="task" 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44.04 12.95 55.12 32h209.76c11.08-19.05 31.49-32 55.12-32 35.35 0 64 28.65 64 64s-28.65 64-64 64c-.35 0-.67-.09-1.02-.1l-39.2 65.32c5.08 9.17 8.22 19.56 8.22 30.78s-3.15 21.61-8.22 30.78l39.2 65.32c.35 0 .67-.1 1.02-.1zm-288 8.88c8.074 4.689 18.432 15.046 23.12 23.12h208.36l-38.46-64.1c-.35 0-.67.1-1.02.1-35.35 0-64-28.65-64-64s28.65-64 64-64c.35 0 .67.09 1.02.1l38.46-64.1H119.12c-4.69 8.073-15.048 18.43-23.12 23.12v209.76zm176-104.88c0 8.82 7.18 16 16 16s16-7.18 16-16-7.18-16-16-16-16 7.18-16 16zm128-160c0-8.82-7.18-16-16-16s-16 7.18-16 16 7.18 16 16 16 16-7.18 16-16zm-336-16c-8.82 0-16 7.18-16 16s7.18 16 16 16 16-7.18 16-16-7.18-16-16-16zm-16 336c0 8.82 7.18 16 16 16s16-7.18 16-16-7.18-16-16-16-16 7.18-16 16zm336 16c8.82 0 16-7.18 16-16s-7.18-16-16-16-16 7.18-16 16 7.18 16 16 16z"/></svg></span> <span>Graphs</span> </span> </a> </div> <div class="dataset-title mb-3"> <div class="row"> <div class="col-md-12"> <div class="float-right dataset-edit"> <div class="dropdown edit-button"> <a data-bs-toggle="modal" data-bs-target="#loginModal"> <span class="badge badge-method-edit" style="padding-top:10px;"><span class=" icon-wrapper icon-fa icon-fa-solid" data-name="edit"><svg viewBox="0 0 576 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M402.6 85.198l90.2 90.2c3.8 3.8 3.8 10 0 13.8l-218.399 218.4-92.8 10.3c-12.4 1.4-22.9-9.1-21.5-21.5l10.3-92.8 218.4-218.4c3.799-3.8 10-3.8 13.799 0zm162-22.9c15.2 15.2 15.2 39.9 0 55.2l-35.4 35.4c-3.8 3.8-10 3.8-13.8 0l-90.2-90.2c-3.8-3.8-3.8-10 0-13.8l35.4-35.4c15.3-15.2 40-15.2 55.2 0zM384 348.198c0-3.2 1.3-6.2 3.5-8.5l40-40c7.6-7.5 20.5-2.2 20.5 8.5v157.8c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48v-352c0-26.5 21.5-48 48-48h285.8c10.7 0 16.1 12.9 8.5 20.5l-40 40c-2.3 2.2-5.3 3.5-8.5 3.5H64v320h320v-101.8z"/></svg></span> Edit</span> </a> </div> </div> <h1 > WN18RR </h1> <span class="dataset-subtitle">Introduced by Bordes et al. in <a href="/paper/translating-embeddings-for-modeling-multi">Translating Embeddings for Modeling Multi-relational Data</a></span> </div> </div> </div> <div class="d-md-none mb-3"> <a href="https://production-assets.paperswithcode.com/perf/images/default_dataset-efab89e8.jpeg" data-lightbox="imageresource-mobile"> <img id="imageresource-mobile" class="d-md-none" src="https://production-assets.paperswithcode.com/perf/images/default_dataset-efab89e8.jpeg"> </a> </div> <div class="dataset-content"> <div class="row"> <div class="col-md-9 description"> <div class="description-content"> <p><strong>WN18RR</strong> is a link prediction dataset created from WN18, which is a subset of WordNet. WN18 consists of 18 relations and 40,943 entities. However, many text triples are obtained by inverting triples from the training set. Thus the WN18RR dataset is created to ensure that the evaluation dataset does not have inverse relation test leakage. In summary, WN18RR dataset contains 93,003 triples with 40,943 entities and 11 relation types.</p> <span class="description-source"> Source: <a href="https://arxiv.org/abs/1811.04441"><span class=" icon-wrapper icon-ion" data-name="document-outline"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M416 221.25V416a48 48 0 0 1-48 48H144a48 48 0 0 1-48-48V96a48 48 0 0 1 48-48h98.75a32 32 0 0 1 22.62 9.37l141.26 141.26a32 32 0 0 1 9.37 22.62z" fill="none" stroke="#000" stroke-linejoin="round" stroke-width="32"/><path d="M256 56v120a32 32 0 0 0 32 32h120" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32"/></svg></span> End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion</a> </span> </div> <div class="context"> <div class="row"> <div class="col-md-12"> <a href="https://download.microsoft.com/download/8/7/0/8700516A-AB3D-4850-B4BB-805C515AECE1/FB15K-237.2.zip" onclick="captureOutboundLink('https://download.microsoft.com/download/8/7/0/8700516A-AB3D-4850-B4BB-805C515AECE1/FB15K-237.2.zip'); return true;" class="btn btn-primary-outline dataset-homepage"> Homepage </a> </div> </div> </div> <div id="benchmarks" class="collapsed"> <h4>Benchmarks <div class="float-right"> <div class="dropdown edit-button"> <button class="dropdown-toggle badge badge-edit" type="button" id="evalEditMenu" data-bs-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> <span class=" icon-wrapper icon-fa icon-fa-solid" data-name="edit"><svg viewBox="0 0 576 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M402.6 85.198l90.2 90.2c3.8 3.8 3.8 10 0 13.8l-218.399 218.4-92.8 10.3c-12.4 1.4-22.9-9.1-21.5-21.5l10.3-92.8 218.4-218.4c3.799-3.8 10-3.8 13.799 0zm162-22.9c15.2 15.2 15.2 39.9 0 55.2l-35.4 35.4c-3.8 3.8-10 3.8-13.8 0l-90.2-90.2c-3.8-3.8-3.8-10 0-13.8l35.4-35.4c15.3-15.2 40-15.2 55.2 0zM384 348.198c0-3.2 1.3-6.2 3.5-8.5l40-40c7.6-7.5 20.5-2.2 20.5 8.5v157.8c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48v-352c0-26.5 21.5-48 48-48h285.8c10.7 0 16.1 12.9 8.5 20.5l-40 40c-2.3 2.2-5.3 3.5-8.5 3.5H64v320h320v-101.8z"/></svg></span> Edit </button> <div class="dropdown-menu dropdown-menu-end" aria-labelledby="evalEditMenu"> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="add"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M256 112v288m144-144H112"/></svg></span> Add a new result</a> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="create-outline"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M384 224v184a40 40 0 0 1-40 40H104a40 40 0 0 1-40-40V168a40 40 0 0 1 40-40h167.48" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32"/><path d="M459.94 53.25a16.06 16.06 0 0 0-23.22-.56L424.35 65a8 8 0 0 0 0 11.31l11.34 11.32a8 8 0 0 0 11.34 0l12.06-12c6.1-6.09 6.67-16.01.85-22.38zM399.34 90L218.82 270.2a9 9 0 0 0-2.31 3.93L208.16 299a3.91 3.91 0 0 0 4.86 4.86l24.85-8.35a9 9 0 0 0 3.93-2.31L422 112.66a9 9 0 0 0 0-12.66l-9.95-10a9 9 0 0 0-12.71 0z"/></svg></span> Link an existing benchmark</a> </div> </div> </div> </h4> <hr> <div class="sota-table-preview"> <table id="benchmarks-table" class="table-striped"> <thead> <tr> <th>Trend</th> <th>Task</th> <th>Dataset Variant</th> <th>Best Model</th> <th>Paper</th> <th>Code</th> </tr> </thead> <tbody> <tr onclick="window.location='/sota/link-prediction-on-wn18rr';"> <td> <a href="/sota/link-prediction-on-wn18rr"> <img class="sota-thumb" src="https://production-media.paperswithcode.com/sota-thumbs/link-prediction-on-wn18rr-small_b6c5fdc6.png"/> </a> </td> <td> <div class="task black-links"> <a style="font-weight: 600;" href="/sota/link-prediction-on-wn18rr"> Link Prediction </a> </div> </td> <td> <div style="font-weight: 500;"> WN18RR </div> </td> <td> <div class="method-name" style="font-weight: 500;"> KERMIT </div> </td> <td> <div class="text-center paper"> <a href="/paper/kermit-knowledge-graph-completion-of-enhanced"> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> </a> </div> </td> <td> <div class="text-center github"><a href="/paper/kermit-knowledge-graph-completion-of-enhanced#code"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </a></div> </td> </tr> <tr onclick="window.location='/sota/knowledge-graph-completion-on-wn18rr';"> <td> <a href="/sota/knowledge-graph-completion-on-wn18rr"> <img class="sota-thumb" src="https://production-media.paperswithcode.com/sota-thumbs/knowledge-graph-completion-on-wn18rr-small_d648c33b.png"/> </a> </td> <td> <div class="task black-links"> <a style="font-weight: 600;" href="/sota/knowledge-graph-completion-on-wn18rr"> Knowledge Graph Completion </a> </div> </td> <td> <div style="font-weight: 500;"> WN18RR </div> </td> <td> <div class="method-name" style="font-weight: 500;"> HAKE </div> </td> <td> <div class="text-center paper"> <a href="/paper/learning-hierarchy-aware-knowledge-graph"> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> </a> </div> </td> <td> <div class="text-center github"><a href="/paper/learning-hierarchy-aware-knowledge-graph#code"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </a></div> </td> </tr> <tr onclick="window.location='/sota/ancestor-descendant-prediction-on-wn18rr';"> <td> <a href="/sota/ancestor-descendant-prediction-on-wn18rr"> <img class="sota-thumb" src="https://production-media.paperswithcode.com/sota-thumbs/ancestor-descendant-prediction-on-wn18rr-small_b7c03503.png"/> </a> </td> <td> <div class="task black-links"> <a style="font-weight: 600;" href="/sota/ancestor-descendant-prediction-on-wn18rr"> Ancestor-descendant prediction </a> </div> </td> <td> <div style="font-weight: 500;"> WN18RR </div> </td> <td> <div class="method-name" style="font-weight: 500;"> ConE </div> </td> <td> <div class="text-center paper"> <a href="/paper/modeling-heterogeneous-hierarchies-with"> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> </a> </div> </td> <td> <div class="text-center github"><a href="/paper/modeling-heterogeneous-hierarchies-with#code"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </a></div> </td> </tr> </tbody> </table> </div> </div> <div id="papers" class="dataset-papers"> <h4 style="margin-bottom: 0.5rem">Papers</h4> <hr> <div class="sota-table-preview papers-datatable-component"> <table style="width: 100% !important;" id="datatable-papers" class="table-striped table-responsive"> <thead style="width: 100% !important;"> <tr> <th style="text-left"><span>Paper</span></th> <th class="text-center"><span>Code</span></th> <th class="text-center"><span>Results</span></th> <th class="text-right"><span>Date</span></th> <th class="text-center"><span>Stars</span></th> </tr> </thead> </table> </div> <script> const DATATABLE_PAPERS_FILTER_NAME = 'paperdataset__dataset_id'; const DATATABLE_PAPERS_FILTER_VALUE = '745'; </script> </div> <div class="dataloader-container"> <div> <h4> Dataset Loaders <div class="float-right"> <div class="dropdown edit-button" style="position: relative; top: -5px"> <button class="dropdown-toggle badge badge-edit" type="button" id="loaderEditMenu" data-bs-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> <span class=" icon-wrapper icon-fa icon-fa-solid" data-name="edit"><svg viewBox="0 0 576 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M402.6 85.198l90.2 90.2c3.8 3.8 3.8 10 0 13.8l-218.399 218.4-92.8 10.3c-12.4 1.4-22.9-9.1-21.5-21.5l10.3-92.8 218.4-218.4c3.799-3.8 10-3.8 13.799 0zm162-22.9c15.2 15.2 15.2 39.9 0 55.2l-35.4 35.4c-3.8 3.8-10 3.8-13.8 0l-90.2-90.2c-3.8-3.8-3.8-10 0-13.8l35.4-35.4c15.3-15.2 40-15.2 55.2 0zM384 348.198c0-3.2 1.3-6.2 3.5-8.5l40-40c7.6-7.5 20.5-2.2 20.5 8.5v157.8c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48v-352c0-26.5 21.5-48 48-48h285.8c10.7 0 16.1 12.9 8.5 20.5l-40 40c-2.3 2.2-5.3 3.5-8.5 3.5H64v320h320v-101.8z"/></svg></span> Edit </button> <div class="dropdown-menu dropdown-menu-end" aria-labelledby="loaderEditMenu"> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="add"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M256 112v288m144-144H112"/></svg></span> Add</a> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="remove"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M400 256H112"/></svg></span> Remove</a> </div> </div> </h4> <hr> </div> <div class="row"> <div class="col-md-12"> <ul class="dataloader-implementations"> <div class="row"> <div class="col-md-7"> <div class="datal-impl-cell"> <a class="code-table-link" href="https://pytorch-geometric.readthedocs.io/en/latest/modules/datasets.html" onclick="captureOutboundLink('https://pytorch-geometric.readthedocs.io/en/latest/modules/datasets.html'); return true;" target="_blank"> <!-- library as icon --> <div class="dataloader-logo text-center"> <svg xmlns="http://www.w3.org/2000/svg" xmlns:vectornator="http://vectornator.io" viewBox="0 0 212.126 230.829" fill-rule="evenodd" clip-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"><g stroke="#591c10" stroke-width="2.3" vectornator:layerName="Untitled"><path d="M74.383 8.494l-51.48 63.36 110.88-35.64-59.4-27.72z" fill="#c03d24"/><path d="M22.903 71.854l79.2 71.28 31.68-106.92-110.88 35.64z" fill="#e6492a"/><path d="M205.063 127.294l-67.32 95.04-35.64-79.2 102.96-15.84z" fill="#cc4126"/><path d="M22.903 71.854l-15.84 31.68 15.84 83.16V71.854z" fill="#902e1b"/><path d="M22.903 71.854l79.2 71.28-79.2 43.56V71.854z" fill="#c53f24"/><path d="M22.903 186.694l114.84 35.64-35.64-79.2-79.2 43.56z" fill="#b53a21"/><path d="M102.103 143.134l31.68-106.92 71.28 91.08-102.96 15.84z" fill="#e94b2b"/><path d="M205.063 127.294l-15.84 35.64-51.48 59.4 67.32-95.04z" fill="#932f1b"/><path d="M133.783 36.214l71.28 91.08-15.84-83.16-55.44-7.92z" fill="#c73f25"/><path d="M74.383 8.494l59.4 27.72 55.44 7.92-114.84-35.64z" fill="#ae3720"/></g></svg> </div> rusty1s/pytorch_geometric </a> </div> </div> <div class="col-3"> <div class="datal-impl-cell text-nowrap"> <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> 21,465 </div> </div> <div class="col-md-2"> <div 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3.5H64v320h320v-101.8z"/></svg></span> Edit </button> </div> </h4> <hr> </div> <div class="row"> <div class="col-md-12"> <ul class="list-unstyled"> <li> <a href="/task/link-prediction"> <span class="badge badge-primary"> <img src="https://production-media.paperswithcode.com/thumbnails/task/task-0000000031-326cd034.jpg"> <span>Link Prediction</span> </span> </a> </li> <li> <a href="/task/knowledge-graph-completion"> <span class="badge badge-primary"> <img src="https://production-media.paperswithcode.com/tasks/default.gif"> <span>Knowledge Graph Completion</span> </span> </a> </li> <li> <a href="/task/ancestor-descendant-prediction"> <span class="badge badge-primary"> <img src="https://production-media.paperswithcode.com/tasks/default.gif"> <span>Ancestor-descendant prediction</span> </span> </a> </li> </ul> </div> </div> <div class="dataset-similar"> <h4> Similar Datasets </h4> <hr> </div> <div class="row"> <div class="col dataset-similar"> <div class="row"> <div class="col-md-12 featured-dataset"> <div class="card-deck card-break" style="margin-bottom:20px;"> <div class="card" style="min-height:120px"> <a href="/dataset/fb15k-237"> <div class="row"> <div class="col-lg-12"> <div class="item-image" style="background-color: #90B06D;opacity: 0.3;"> <span class="dataset-img-icon"><span class=" icon-wrapper icon-fa icon-fa-solid" data-name="draw-polygon"><svg viewBox="0 0 448 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M384 353.998c35.35 0 64 28.65 63.99 64 0 35.35-28.65 64-64 64-23.63 0-44.03-12.95-55.12-32H119.12c-11.08 19.05-31.49 32-55.12 32-35.35 0-64-28.65-64-64 0-23.63 12.95-44.04 32-55.13v-209.75c-19.05-11.08-32-31.49-32-55.12 0-35.35 28.65-64 64-64 23.63 0 44.04 12.95 55.12 32h209.76c11.08-19.05 31.49-32 55.12-32 35.35 0 64 28.65 64 64s-28.65 64-64 64c-.35 0-.67-.09-1.02-.1l-39.2 65.32c5.08 9.17 8.22 19.56 8.22 30.78s-3.15 21.61-8.22 30.78l39.2 65.32c.35 0 .67-.1 1.02-.1zm-288 8.88c8.074 4.689 18.432 15.046 23.12 23.12h208.36l-38.46-64.1c-.35 0-.67.1-1.02.1-35.35 0-64-28.65-64-64s28.65-64 64-64c.35 0 .67.09 1.02.1l38.46-64.1H119.12c-4.69 8.073-15.048 18.43-23.12 23.12v209.76zm176-104.88c0 8.82 7.18 16 16 16s16-7.18 16-16-7.18-16-16-16-16 7.18-16 16zm128-160c0-8.82-7.18-16-16-16s-16 7.18-16 16 7.18 16 16 16 16-7.18 16-16zm-336-16c-8.82 0-16 7.18-16 16s7.18 16 16 16 16-7.18 16-16-7.18-16-16-16zm-16 336c0 8.82 7.18 16 16 16s16-7.18 16-16-7.18-16-16-16-16 7.18-16 16zm336 16c8.82 0 16-7.18 16-16s-7.18-16-16-16-16 7.18-16 16 7.18 16 16 16z"/></svg></span></span> <span class="dataset-img-text">FB15k-237</span> </div> </div> </div> <div class=row"> <h1>FB15k-237</h1> </div> </a> </div> <div class="card" style="min-height:120px"> <a href="/dataset/umls"> <div class="row"> <div class="col-lg-12"> <div class="item-image" style="background-color: #CD933C;opacity: 0.3;"> <span class="dataset-img-icon"><span class=" icon-wrapper icon-fa icon-fa-solid" data-name="font-case"><svg viewBox="0 0 640 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M229.88 87.688l121.28 341.2c.462 1.372.838 3.661.838 5.11 0 8.83-7.167 15.999-15.998 16h-50.62c-6.343-.001-13.134-4.88-15.16-10.89l-19.07-53.11h-150.3l-19.07 53.11c-2.026 6.01-8.817 10.889-15.16 10.89H16c-8.825-.007-15.989-7.175-15.989-16 0-1.448.376-3.738.838-5.11l121.271-341.2c4.075-11.973 17.647-21.69 30.294-21.69h47.172c12.648 0 26.22 9.717 30.294 21.69zm-100.3 218.31h92.84L176 176.738zm494.42-144c8.832 0 16 7.168 16 16v256c0 8.832-7.168 16-16 16h-32c-8.832 0-16-7.168-16-16v-1.81c-18.9 11.03-40.58 17.81-64 17.81-70.58-.077-127.923-57.42-128-128v-32c.077-70.579 57.42-127.923 128-128 23.42 0 45.1 6.81 64 17.81v-1.81c0-8.832 7.168-16 16-16h32zm-64 160v-32c0-26.496-21.504-48-48-48s-48 21.504-48 48v32c0 26.496 21.504 48 48 48s48-21.504 48-48z"/></svg></span></span> <span class="dataset-img-text">UMLS</span> </div> </div> </div> <div class=row"> <h1>UMLS</h1> </div> </a> </div> <div class="card" style="min-height:120px"> <a href="/dataset/nell-995"> <div class="row"> <div class="col-lg-12"> <div class="item-image" style="background-color: #A59F78;opacity: 0.3;"> <span class="dataset-img-icon"><span class=" icon-wrapper icon-fa icon-fa-solid" data-name="file"><svg viewBox="0 0 384 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M224 137.998c0 13.2 10.8 24 24 24h136v328c0 13.3-10.7 24-24 24H24c-13.3 0-24-10.7-24-24v-464c0-13.3 10.7-24 24-24h200v136zm160-14.1v6.1H256v-128h6.1c6.4 0 12.5 2.5 17 7l97.9 98c4.5 4.5 7 10.6 7 16.9z"/></svg></span></span> <span class="dataset-img-text">NELL-995</span> </div> </div> </div> <div class=row"> <h1>NELL-995</h1> </div> </a> </div> <div class="card" style="min-height:120px"> <a href="/dataset/fb15k"> <div class="row"> <div class="col-lg-12"> <div class="item-image" style="background-image: url(https://production-media.paperswithcode.com/datasets/Screen_Shot_2021-01-28_at_6.26.00_PM.png);"> </div> </div> </div> <div class=row"> <h1>FB15k</h1> </div> </a> </div> </div> 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