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<!DOCTYPE html>
<html lang="en">
<head>
<meta http-equiv="content-type" content="text/html; charset=ISO-8859-1"/>
<meta name="viewport" content="width=device-width, initial-scale=1"/>
<title>Semantic Web Challenge on Tabular Data to Knowledge Graph Matching</title>
<link rel="stylesheet" type="text/css" href="style.css"/>
<link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css"
rel="stylesheet"
integrity="sha384-0evHe/X+R7YkIZDRvuzKMRqM+OrBnVFBL6DOitfPri4tjfHxaWutUpFmBp4vmVor"
crossorigin="anonymous"/>
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</head>
<body>
<nav id="navbar" class="navbar navbar-expand-lg bg-light sticky-top">
<div class="container-fluid">
<span class="navbar-brand mb-0 h1">SemTab 2022</span>
<button class="navbar-toggler"
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<ul class="navbar-nav me-auto mb-2 mb-lg-0">
<li class="nav-item">
<a class="nav-link" href="#about">About</a>
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<li class="nav-item">
<a class="nav-link" href="#program">Program</a>
</li>
<li class="nav-item">
<a class="nav-link" href="#forum">Participate!</a>
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Tracks
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<li>
<a class="dropdown-item" href="#artifacts-track">Artifacts Availability Badge</a>
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Datasets and Tasks
</a>
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<li>
<a class="dropdown-item" href="#round1">Round #1</a>
</li>
<li>
<a class="dropdown-item" href="#round2">Round #2</a>
</li>
<li>
<a class="dropdown-item" href="#round3">Round #3</a>
</li>
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<a class="nav-link" href="#results">Results</a>
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<a class="nav-link" href="#paper">Paper Guidelines</a>
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<a class="nav-link" href="#organisation">Organisation</a>
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<a class="nav-link" href="#acknowledgements">Acknowledgements</a>
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<span class="navbar-text">Semantic Web Challenge on Tabular Data to Knowledge Graph Matching</span>
</div>
</div>
</nav>
<!--<div class="alert alert-warning" role="alert">-->
<!-- <b>News (09/03/2022):</b> The <a class="alert-link" href="http://ceur-ws.org/Vol-3103/" target="_blank">SemTab 2021 proceedings</a> are out. <a href="#results" class="alert-link">Results</a> and <a href="#gt" class="alert-link">ground</a> truths are available.-->
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data-bs-spy="scroll"
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<h2 class="title display-6" id="about">
<i class="bi bi-trophy"></i>
About the Challenge
</h2>
<p>
Tabular data in the form of CSV files is the common input format in
a data analytics pipeline. However, a lack of understanding of the
semantic structure and meaning of the content may hinder the data
analytics process. Thus gaining this semantic understanding will be
very valuable for data integration, data cleaning, data mining,
machine learning and knowledge discovery tasks. For example,
understanding what the data is can help assess what sorts of
transformation are appropriate on the data.
</p>
<p>
Tables on the Web may also be the source of highly valuable data.
The addition of semantic information to Web tables may enhance a
wide range of applications, such as web search, question answering,
and knowledge base (KB) construction.
</p>
<p>
Tabular data to Knowledge Graph (KG) matching is the process of
assigning semantic tags from Knowledge Graphs (e.g., Wikidata or
DBpedia) to the elements of the table. This task however is often
difficult in practice due to metadata (e.g., table and column names)
being missing, incomplete or ambiguous.
</p>
<p>
The <a href="http://www.cs.ox.ac.uk/isg/challenges/sem-tab/">SemTab challenge</a>
aims at benchmarking systems dealing with the tabular data to KG
matching problem, so as to facilitate their comparison on the same
basis and the reproducibility of the results.
</p>
<p>
The <b>2022 edition</b> of this challenge will be collocated with the
<a href="https://iswc2022.semanticweb.org/" target="_blank">
21st International Semantic Web Conference
</a>
and the
<a href="http://om2022.ontologymatching.org/" target="_blank"
>17th International Workshop on Ontology Matching</a
>.
</p>
<h2 class="title display-6 pt-5" id="proceedings">
<i class="bi bi-book"></i>
Proceedings
</h2>
<p> SemTab papers have been published as a <a href="https://ceur-ws.org/Vol-3320/" target="_blank">volume 3320 of CEUR-WS</a>.
</p>
<!-- Preliminary version of the system and dataset papers
are available <a href="https://drive.google.com/drive/folders/1T7euw-3eEhF2XcHHTuu6HHgsz0kElJ6S?usp=sharing" target="_blank">here</a>.
-->
<h2 class="title display-6 pt-5" id="program">
<i class="bi bi-calendar-event"></i>
Program during ISWC
</h2>
<p>
There will be two session associated to the SemTab challenge on Tuesday and a space devoted to the challenge during the ISWC poster session on Wedesday:
<a href="https://iswc2022.semanticweb.org/index.php/conference/" target="_blank">ISWC program</a>. Videos of the talks are available
<a href="https://drive.google.com/drive/folders/1h53fxZZhIUMStFF9G102OWeJ9-ymPulB?usp=sharing" target="_blank">here</a>.
</p>
<p> <b>Tuesday, October 25, ISWC session 11:40-12:40 (CEST)</b>. In parallel with Main Track 1A and 1B.<p>
<ul>
<li>Introduction from the organisers (15 min)</li>
<li>DAGOBAH system presented by Viet Phi HUYNH (10+5 min).</li>
<li>KGCODE-Tab system by Xinhe Li (10+5min)</li>
<li>Wikary dataset presented by Benno Kruit (10+5 min)</li>
</ul>
<p> <b>Tuesday, October 25, ISWC session 12:50-13:50 (CEST)</b>. In parallel with Main Track 2A and 2B.<p>
<ul>
<li>SOTAB dataset presented by Keti Korini (10+5 min)</li>
<li>s-elBat presented by Roberto Avogadro (5+2 min)</li>
<li>MammoTab presented by Mattia Marzocchi (5+2 min)</li>
<li>TSOTSA presented by Brice Foko (5+2 min)</li>
<li>Food composition dataset presented by Folefac Martins (5+2 min)</li>
<li>Closure and announcement of awards by the organisers (15 min)</li>
</ul>
<p> <b>Wednesday, October 26, ISWC Poster and demo session: 11:40-13:50 (CEST)</b>. Look for the SemTab room in <a href="https://app.gather.town/invite?token=f3a4Td2dTcCp_wKRz5r2" target="_blank">gather.town</a>. Posters available <a href="https://drive.google.com/drive/folders/1ynk0UfJ3nd0QeIzgDxtB8Q5yzD3SB5Bz?usp=sharing">here</a>.</p>
<h2 class="title display-6 pt-5" id="forum">
<i class="bi bi-chat-square-text"></i>
Participation: Forum and Registration
</h2>
<p>
We have a
<a href="https://groups.google.com/d/forum/sem-tab-challenge" target="_blank">discussion group</a>
for the challenge where we share the latest news with the
participants and we discuss issues risen during the evaluation
rounds.
</p>
<p>
Please register your system using this
<a href="https://bit.ly/semtab2022-participation" target="_blank">google form</a>.
</p>
<p>
Note that participants can join SemTab at any Round for any of the
tasks/tracks.
</p>
<h2 class="title display-6 pt-5" id="tracks">
<i class="bi bi-layout-wtf"></i>
Challenge Tracks
</h2>
<h3 class="pt-4" id="accuracy-track">Accuracy Track</h3>
The evaluation of systems regarding accuracy is similar to prior
versions of the SemTab.<br/>
That is, to illustrate the accuracy of the submissions, we evaluate
systems on typical multi-class classification metrics as detailed
below.<br/>
In addition, we adopt the "cscore" for the CTA task to reflect the
distance in the type hierarchy between the predicted column type and
the ground truth semantic type.<br/>
<br/>
<br/>
Matching Tasks:
<ul>
<li>
<b>CTA Task</b>: Assigning a semantic type (a DBpedia class as
fine-grained as possible) to a column.
</li>
<li><b>CEA Task</b>: Matching a cell to a Wikidata entity.</li>
<li>
<b>CPA Task</b>: Assigning a KG property to the relationship
between two columns.
</li>
</ul>
Matching Criteria:
<ul>
<li>Average Precision</li>
<li>Average Recall</li>
<li>Average F1</li>
<li>Cscore</li>
</ul>
Important Dates (all 2022, deadlines 11:59pm AoE):
<ul>
<li><b>May 26:</b> First call for challenge participants.</li>
<li><b>June 13 - July 14:</b> Round 1.</li>
<li><b>July 18 - September 1:</b> Round 2.</li>
<li>
<b>August 15:</b> Inivations to present at the
<a href="https://iswc2022.semanticweb.org/" target="_blank"
>ISWC conference</a
>.
</li>
<li><b>September 19 - October 15:</b> Round 3.</li>
<li>
<b>October 21</b>: Paper submissions (via <a
href="https://easychair.org/conferences/?conf=semtab2022" target="_blank">easychair</a>), and
artifact
publication.
</li>
<li>
<b>October 23 - 27</b>: Challenge presentation during OM workshop.
</li>
<li>
<b>October 23 - 27</b>: Challenge Presentation and prize
announcement during ISWC.
</li>
<li><b>November <s>15</s> 22</b>: Final version papers (via <a
href="https://easychair.org/conferences/?conf=semtab2022" target="_blank">easychair</a>).
</li>
</ul>
<h3 class="pt-4" id="datasets-track">Datasets Track</h3>
The data that table-to-Knowledge-Graph matching systems are trained
and evaluated on, is critical for their accuracy and relevance.<br/>
We invite dataset submissions that provide challenging and accessible
new datasets to advance the state-of-the-art of table-to-KG matching
systems.<br/>
Preferably, these datasets provide tables along with their ground
truth annotations for at least one of CEA, CTA and CPA tasks.<br/>
The dataset may be general or specific to a certain domain.<br/>
<br/>
Submissions will be evaluated according to provide the following:
<ul>
<li>
Description of the data collection, curation, and annotation
processes.
</li>
<li>
Availability of documentation with insights in the dataset
content.
</li>
<li>
Publicly accessible link to the dataset (e.g. Zenodo) and its DOI.
</li>
<li>Explanation of maintenance and long-term availability.</li>
<li>Clear description of the envisioned use-cases.</li>
<li>
Application in which the dataset is used to solve an exemplar
task.
</li>
</ul>
We ask participants to describe their datasets submissions via
<a href="https://easychair.org/conferences/?conf=semtab2022" target="_blank">easychair</a>
in a short paper (max 6 pages) that discusses how the above
criteria are covered, while also including a link to the resources.
The link to the resources may be private, until the submission is
evaluated by the SemTab organisers. See paper guidelines below, for
more details. More guidance for creating, documenting and publishing
datasets can be found
<a
href="https://neurips.cc/Conferences/2022/CallForDatasetsBenchmarks"
target="_blank"
>here</a
>.
<br/>
<br/>
Important Dates:
<ul>
<li>
<b>August <s>15</s> 25:</b> Paper submissions (via <a
href="https://easychair.org/conferences/?conf=semtab2022" target="_blank">easychair</a>), and
artifact
publication.
</li>
<li><b>September 30:</b> Notification of accept/reject.</li>
<li>
<b>October 23 - 27</b>: Dataset Presentation and prize
announcement during ISWC.
</li>
<li><b>November <s>15</s> 22</b>: Final version papers (via <a
href="https://easychair.org/conferences/?conf=semtab2022" target="_blank">easychair</a>).
</li>
</ul>
<h3 class="pt-4" id="artifacts-track">Artifacts Availability Badge</h3>
New this year is the Artifacts Availability Badge which is applicable
to the Accuracy Track as well as the Datasets Track.<br/>
The goal of this badge is to motivate authors to publish and document
their systems, code, and data, so that others can use these artifacts
and potentially reproduce or build on the results.<br/>
This badge is given if all resources are verified to satisfy the below
criteria.<br/>
<br/>
The criteria used to assess submissions (both accuracy and dataset
submissions) are:
<ul>
<li>Publicly accessible data (if applicable).</li>
<li>Publicly accessible source code.</li>
<li>Clear documentation of the code and data.</li>
<li>Open-source dependencies.</li>
</ul>
<!-- BELOW FROM 2020: -->
<!-- <p>
The challenge will be run with the support of the
<a href="https://www.aicrowd.com/challenges/semtab-2021" target="_blank">AICrowd platform</a> and the <a href="https://bitbucket.org/disco_unimib/stiltool/" target="_blank">STILTool system</a>.</p>
-->
<h2 class="title display-6 pt-5" id="tasks">
<i class="bi bi-table"></i>
Datasets and tasks per round
</h2>
<h3 class="pt-4" id="round1">Round #1</h3>
<ul class="nav nav-tabs mb-3" id="round1-tasks-tab" role="tablist">
<li class="nav-item" role="presentation">
<button
class="nav-link active"
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CTA-WD (Round #1)
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<h4>Column Type Annotation by Wikidata (CTA-WD)</h4>
<p>
This is a task of ISWC 2022 "Semantic Web Challenge on Tabular Data to Knowledge Graph
Matching".
It's to annotate an entity column (i.e., a column composed of entity mentions) in a table with
types from <strong>Wikidata</strong>
(version: <a href="https://zenodo.org/record/6643443">20220521</a>) <br>
<i class="bi bi-lightbulb-fill" style="color: var(--bs-yellow)"></i>
Notes: participants may use the public Wikidata endpoint (or its API) since the above dump is
very recent.
</p>
<h5>Task Description</h5>
<p>
The task is to annotate each entity column by items of Wikidata as its type.
Each column can be annotated by multiple types:
the one that is as fine grained as possible and correct to all the column cells, is regarded as
a <strong>perfect annotation</strong>;
the one that is the ancestor of the perfect annotation is regarded as an <strong>okay
annotation</strong>;
others are regarded as <strong>wrong annotations</strong>.
</p>
<p>
The annotation can be a normal entity of Wikidata, with the prefix of
http://www.wikidata.org/entity/, such as http://www.wikidata.org/entity/Q8425. Each column
should be annotated by <strong>at most one item</strong>. A perfect annotation is encouraged
with a full score,
while an okay annotation can still get a part of the score. Example:
"KIN0LD6C","0","http://www.wikidata.org/entity/Q8425". Please use the prefix of
http://www.wikidata.org/entity/ instead of the URL prefix https://www.wikidata.org/wiki/.
</p>
<p>
The annotation should be represented by its full IRI, where the case is NOT sensitive. Each
submission should be a CSV file. Each line should include a column identified by table id and
column id, and the column's annotation (a Wikidata item). It means one line should include three
fields: "Table ID", "Column ID" and "Annotation IRI". The headers should be excluded from the
submission file.
</p>
Notes:
<ol>
<li>
Table ID is the filename of the table data, but does NOT include the extension.
</li>
<li>
Column ID is the position of the column in the input, starting from 0, i.e., first column's
ID is 0.
</li>
<li>
One submission file should have NO duplicate lines for each target column.
</li>
<li>
Annotations for columns out of the target columns are ignored.
</li>
</ol>
<h5>Dataset</h5>
<dl class="row">
<dt class="col-sm-3">Link</dt>
<dd class="col-sm-9"><a
href="https://github.com/sem-tab-challenge/2022/blob/main/datasets/HardTablesR1.tar.gz"
target="_blank">Round #1 HardTables Dataset</a></dd>
<dt class="col-sm-3">Description</dt>
<dd class="col-sm-9">
<p>The dataset contains:</p>
<ul>
<li>evaluator codes (CTA_WD_Evaluator.py)</li>
<li>the validation set (DataSets/HardTablesR1/Valid/gt/cta_gt.csv,
DataSets/HardTablesR1/Valid/gt/cta_gt_ancestor.json,
DataSets/HardTablesR1/Valid/gt/cta_gt_descendent.json,
DataSets/HardTablesR1/Valid/tables)
</li>
<li>the testing set (DataSets/HardTablesR1/Test/tables,
DataSets/HardTablesR1/Test/target/cta_gt.csv)
</li>
</ul>
</dd>
<dt class="col-sm-3">Format</dt>
<dd class="col-sm-9">
One table is stored in one CSV file. Each line corresponds to a table row. The
first row may either be the table header or content. The target columns for annotation are
saved
in a CSV file. The CTA GTs' ancestors and descendents are saved in two json files,
respectively.
</dd>
</dl>
<h5>Evaluation Criteria</h5>
<p>
We encourage one perfect annotation, and at same time score one of its ancestors (okay
annotation). Thus we calculate Approximate Precision (\(APrecision\)), Approximate Recall
(\(ARecall\)), and Approximate F1 Score (\(AF1\)):
\[APrecision = {\sum_{a \in all\ annotations}g(a) \over all\ annotations\ \#}\]
\[ARecall = {\sum_{col \in all\ target\ columns}(max\_annotation\_score(col)) \over all\ target\
columns\ \#}\]
\[AF1 = {2 \times APrecision \times ARecall \over APrecision + ARecall}\]
</p>
Notes:
<ol>
<li>
# denotes the number.
</li>
<li>
\(
g(a) =
\begin{cases}
1.0, & \text{ if } a \text{ is a perfect annotation} \\
0.8^{d(a)}, & \text{ if } a \text{ is an ancestor of the perfect annotation and } d(a) < 5
\\
0.7^{d(a)}, & \text{ if } a \text{ is a descendent of the perfect annotation and } d(a) < 3
\\
0, & otherwise
\end{cases}
\)
<p>
where \(d(a)\) is the depth to the perfect annotation.
E.g., \(d(a)=1\) if \(a\) is a parent of the perfect annotation, and \(d(a)=2\) if \(a\)
is a grandparent of the perfect annotation.
</p>
</li>
<li>
\(
max\_annotation\_score(col) =
\begin{cases}
g(a), & \text{ if } col \text{ has an annotation } a \\
0, & \text{ if } col \text{ has no annotation }
\end{cases}
\)
</li>
<li>
\(AF1\) is used as the primary score, and \(APrecision\) is used as the secondary score.
</li>
<li>
A cell may have multiple equivalent Wikidata items as its GT (e.g., redirected pages
Q20514736 and Q852446). For an annotated entity, our evaluator will calculate the score with
each GT entity and select the maximum score.
</li>
</ol>
<h5>Submission</h5>
Participants can test and develop their systems on the given ground truth (validation set).
They can weekly <a href="https://bit.ly/semtab2022-round1" target="_blank"> upload </a> their
annotations corresponding to the
targets (test set).
<!--https://forms.gle/nrkQqNje6PrpuPGU9-->
</div>
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<h4>Cell Entity Annotation by Wikidata (CEA-WD)</h4>
<p>
This is a task of ISWC 2022 "Semantic Web Challenge on Tabular Data to Knowledge Graph
Matching".
It is to annotate column cells (entity mentions) in a table with entities of
<strong>Wikidata</strong>
(version: <a href="https://zenodo.org/record/6643443">20220521</a>) <br>
<i class="bi bi-lightbulb-fill" style="color: var(--bs-yellow)"></i>
Notes: participants may use the public Wikidata endpoint (or its API) since the above dump is
very recent.
</p>
<h5>Task Description</h5>
<p>
The task is to annotate each target cell with an entity of Wikidata.
Each submission should contain the annotation of the target cell. One cell can be annotated by
one entity with the prefix of http://www.wikidata.org/entity/. Any of the equivalent entities of
the ground truth entity are regarded as correct. Case is NOT sensitive.
</p>
<p>
The submission file should be in CSV format.
Each line should contain the annotation of one cell which is identified by a table id, a column
id and a row id.
Namely one line should have four fields: "Table ID", "Row ID", "Column ID" and "Entity IRI".
Each cell should be annotated by <strong>at most one entity</strong>.
The headers should be excluded from the submission file.
Here is an example: "OHGI1JNY","32","1","http://www.wikidata.org/entity/Q5484".
Please use the prefix of http://www.wikidata.org/entity/ instead of
https://www.wikidata.org/wiki/ which is the prefix of the Wikidata page URL.
</p>
Notes:
<ol>
<li>
Table ID does not include filename extension; make sure you remove the .csv extension from
the filename.
</li>
<li>
Column ID is the position of the column in the table file, starting from 0, i.e., first
column's ID is 0.
</li>
<li>
Row ID is the position of the row in the table file, starting from 0, i.e., first row's ID
is 0.
</li>
<li>
One submission file should have NO duplicate lines for one cell.
</li>
<li>
Annotations for cells out of the target cells are ignored.
</li>
</ol>
<h5>Dataset</h5>
<dl class="row">
<dt class="col-sm-3">Link</dt>
<dd class="col-sm-9"><a
href="https://github.com/sem-tab-challenge/2022/blob/main/datasets/HardTablesR1.tar.gz"
target="_blank">Round #1 HardTables Dataset</a></dd>
<dt class="col-sm-3">Description</dt>
<dd class="col-sm-9">
<p>The dataset contains:</p>
<ul>
<li>evaluator codes (CEA_WD_Evaluator.py)</li>
<li>the validation set (DataSets/HardTablesR1/Valid/gt/cea_gt.csv,
DataSets/HardTablesR1/Valid/tables)
</li>
<li>the testing set (DataSets/HardTablesR1/Test/tables,
DataSets/HardTablesR1/Test/target/cea_target.csv)
</li>
</ul>
</dd>
<dt class="col-sm-3">Format</dt>
<dd class="col-sm-9">
One table is stored in one CSV file. Each line corresponds to a table row. The first row may
either be the table header or content. The target cells for annotation are saved in a CSV
file.
</dd>
</dl>
<h5>Evaluation Criteria</h5>
<p>
Precision, Recall and F1 Score are calculated:
\[Precision = {{correct\_annotations \#} \over {submitted\_annotations \#}}\]
\[Recall = {{correct\_annotations \#} \over {ground\_truth\_annotations \#}}\]
\[F1 = {2 \times Precision \times Recall \over Precision + Recall}\]
</p>
Notes:
<ol>
<li>
# denotes the number.
</li>
<li>
\(F1\) is used as the primary score, and \(Precision\) is used as the secondary score.
</li>
<li>
One target cell, one ground truth annotation, i.e., # ground truth annotations = # target
cells. The ground truth annotation has already covered all equivalent entities (e.g., wiki
page redirected entities); the ground truth is hit if one of its equivalent entities is hit.
</li>
</ol>
<h5>Submission</h5>
Participants can test and develop their systems on the given ground truth (validation set).
They can weekly <a href="https://bit.ly/semtab2022-round1" target="_blank"> upload </a> their annotations corresponding to the
targets (test set).
</div>
<div
class="tab-pane fade"
id="round1-cpa-wd-tab-pane"
role="tabpanel"
aria-labelledby="round1-cpa-wd-tab"
tabindex="0"
>
<h4>Column Property Annotation by Wikidata (CPA-WD)</h4>
<p>
This is a task of ISWC 2022 "Semantic Web Challenge on Tabular Data to Knowledge Graph
Matching".
It is to annotate column relationships in a table with properties of
<strong>Wikidata</strong>
(version: <a href="https://zenodo.org/record/6643443">20220521</a>) <br>
<i class="bi bi-lightbulb-fill" style="color: var(--bs-yellow)"></i>
Notes: participants may use the public Wikidata endpoint (or its API) since the above dump is
very recent.
</p>
<h5>Task Description</h5>
<p>
The task is to annotate each column pair with a property of Wikidata.
Each submission should contain an annotation of a target column pair. Note the order of the two
columns matters. The annotation property should start with the prefix of
http://www.wikidata.org/prop/direct/. Case is NOT sensitive.
</p>
<p>
The submission file should be in CSV format.
Each line should contain the annotation of two columns which is identified by a table id, column
id one and column id two.
Namely one line should have four fields: "Table ID", "Column ID 1", "Column ID 2" and "Property
IRI".
Each column pair should be annotated by <strong>at most one property</strong>.
The headers should be excluded from the submission file.
Here is an example: "OHGI1JNY","0","1","http://www.wikidata.org/prop/direct/P702".
Please use the prefix of http://www.wikidata.org/prop/direct/ instead of
https://www.wikidata.org/wiki/ which is the prefix of the Wikidata page URL.
</p>
Notes:
<ol>
<li>
Table ID does not include filename extension; make sure you remove the .csv extension from
the filename.
</li>
<li>
Column ID is the position of the column in the table file, starting from 0, i.e., first
column's ID is 0.
</li>
<li>
One submission file should have NO duplicate lines for one column pair.
<li>
Annotations for column pairs out of the targets are ignored.
</li>
</ol>
<h5>Dataset</h5>
<dl class="row">
<dt class="col-sm-3">Link</dt>
<dd class="col-sm-9"><a
href="https://github.com/sem-tab-challenge/2022/blob/main/datasets/HardTablesR1.tar.gz"
target="_blank">Round #1 HardTables Dataset</a></dd>
<dt class="col-sm-3">Description</dt>
<dd class="col-sm-9">
<p>The dataset contains:</p>
<ul>
<li>evaluator codes (CPA_WD_Evaluator.py))</li>
<li>the validation set (DataSets/HardTablesR1/Valid/gt/cpa_gt.csv,
DataSets/HardTablesR1/Valid/tables)
</li>
<li>the testing set (DataSets/HardTablesR1/Test/tables,
DataSets/HardTablesR1/Test/target/cpa_target.csv)
</li>
</ul>
</dd>
<dt class="col-sm-3">Format</dt>
<dd class="col-sm-9">
One table is stored in one CSV file. Each line corresponds to a table row. The first row may
either be the table header or content. The target cells for annotation are saved in a CSV
file.
</dd>
</dl>
<h5>Evaluation Criteria</h5>
<p>
Precision, Recall and F1 Score are calculated:
\[Precision = {{correct\_annotations \#} \over {submitted\_annotations \#}}\]
\[Recall = {{correct\_annotations \#} \over {ground\_truth\_annotations \#}}\]
\[F1 = {2 \times Precision \times Recall \over Precision + Recall}\]
</p>
Notes:
<ol>
<li>
# denotes the number.
</li>
<li>
\(F1\) is used as the primary score, and \(Precision\) is used as the secondary score.
</li>
<li>
One target column pair, one ground truth annotation, i.e., # ground truth annotations = #
target column pairs.
</li>
</ol>
<h5>Submission</h5>
Participants can test and develop their systems on the given ground truth (validation set).
They can weekly <a href="https://bit.ly/semtab2022-round1" target="_blank"> upload </a> their annotations corresponding to the
targets (test set).
</div>
</div>
<h3 class="pt-4" id="round2">Round #2</h3>
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<h4>Column Type Annotation by Wikidata (HT-CTA-WD)</h4>
<p>
This is a task of ISWC 2022 "Semantic Web Challenge on Tabular Data to Knowledge Graph
Matching".
It's to annotate an entity column (i.e., a column composed of entity mentions) in a table with
types from <strong>Wikidata</strong>
(version: <a href="https://zenodo.org/record/6643443">20220521</a>) <br>
<i class="bi bi-lightbulb-fill" style="color: var(--bs-yellow)"></i>
Notes: participants may use the public Wikidata endpoint (or its API) since the above dump is
very recent.
</p>
<h5>Task Description</h5>
<p>
The task is to annotate each entity column by items of Wikidata as its type.
Each column can be annotated by multiple types:
the one that is as fine grained as possible and correct to all the column cells, is regarded as
a <strong>perfect annotation</strong>;
the one that is the ancestor of the perfect annotation is regarded as an <strong>okay
annotation</strong>;
others are regarded as <strong>wrong annotations</strong>.
</p>
<p>
The annotation can be a normal entity of Wikidata, with the prefix of
http://www.wikidata.org/entity/, such as http://www.wikidata.org/entity/Q8425. Each column
should be annotated by <strong>at most one item</strong>. A perfect annotation is encouraged
with a full score,
while an okay annotation can still get a part of the score. Example:
"KIN0LD6C","0","http://www.wikidata.org/entity/Q8425". Please use the prefix of
http://www.wikidata.org/entity/ instead of the URL prefix https://www.wikidata.org/wiki/.
</p>
<p>
The annotation should be represented by its full IRI, where the case is NOT sensitive. Each
submission should be a CSV file. Each line should include a column identified by table id and
column id, and the column's annotation (a Wikidata item). It means one line should include three
fields: "Table ID", "Column ID" and "Annotation IRI". The headers should be excluded from the
submission file.
</p>
Notes:
<ol>
<li>
Table ID is the filename of the table data, but does NOT include the extension.
</li>