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@cremarco
cremarco committed Jul 18, 2024
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Expand Up @@ -22,91 +22,95 @@ import HorizontalTimeline from "@components/HorizontalTimeline.astro";
What's Semantic Table Interpretation?
</h2>
<p class="mt-4 mb-6 md:text-base lg:text-base">
Semantic Table Interpretation, as defined by the the <a href="https://sem-tab-challenge.github.io/2023/">SemTab challenge</a>, involves annotating relational
tables with information from a Knowledge Graph (KG). This process
includes associating each column in a table with one or more KG types,
known as Column Type Annotation (CTA). Additionally, Cell Entity
Annotation (CEA) is applied to annotate each cell in named entity columns
with a KG entity or mark it as Not In Lexicon (NIL) if it does not exist in the KG.
Columns Property Annotation (CPA) involves annotating pairs of columns
with a KG property. The result of this annotation process is a
table enriched with semantic information
<p class="mt-4 mb-4 md:text-base lg:text-base"></p>
<Button href="/sti-website/description" variant="secondary">
Learn more about STI
</Button>
<section>
Semantic Table Interpretation, as defined by the the <a
href="https://sem-tab-challenge.github.io/2023/">SemTab challenge</a
>, involves annotating relational tables with information from a
Knowledge Graph (KG). This process includes associating each column in a
table with one or more KG types, known as Column Type Annotation (CTA).
Additionally, Cell Entity Annotation (CEA) is applied to annotate each
cell in named entity columns with a KG entity or mark it as Not In
Lexicon (NIL) if it does not exist in the KG. Columns Property
Annotation (CPA) involves annotating pairs of columns with a KG
property. The result of this annotation process is a table enriched with
semantic information
<p class="mt-4 mb-4 md:text-base lg:text-base"></p>
<Button href="/sti-website/description" variant="secondary">
Learn more about STI
</Button>
<section>
<h2
class="text-3xl font-semibold bg-gradient-to-r from-[#9E0974] to-[#6665E9] inline-block text-transparent bg-clip-text mt-10"
>
TUTSTI @ISWC2024
</h2>
<p class="mb-6 mt-4 md:text-base lg:text-base">
Discover the comprehensive world of Semantic Table Interpretation
(STI) in this tutorial, which covers both theoretical and practical
aspects, and trace the evolution of STI from heuristic-based methods
to machine learning (ML) techniques and the latest large language
model (LLM) innovations. By examining the unique characteristics,
advantages, and limitations of each approach you will understand
their optimal contexts of use
</p>
<div class="flex flex-wrap gap-2">
<Button href="/sti-website/tutorial" variant="secondary">
Learn more about TUTSTI @ ISWC2024
</Button>
<Button
href="https://iswc2024.semanticweb.org/event/3715c6fc-e2d7-47eb-8c01-5fe4ac589a52/summary"
variant="secondary"
className="md:ml-4"
>
ISWC 2024
<img src={logoISWC.src} class="ms-2 w-6 h-6" />
</Button>
</div>
</section>
</p>

<Section className="pt-20">
<h2
class="text-3xl font-semibold bg-gradient-to-r from-[#9E0974] to-[#6665E9] inline-block text-transparent bg-clip-text mt-10"
>
TUTSTI @ISWC2024
Our Approaches, Datasets, Tools and UIs
</h2>
<p class="mb-6 mt-4 md:text-base lg:text-base">
Discover the comprehensive world of Semantic Table Interpretation
(STI) in this tutorial, which covers both theoretical and practical
aspects, and trace the evolution of STI from heuristic-based methods
to machine learning (ML) techniques and the latest large language
model (LLM) innovations. By examining the unique characteristics,
advantages, and limitations of each approach you will understand their
optimal contexts of use
</p>
<div class="flex flex-wrap gap-2">
<Button href="/sti-website/tutorial" variant="secondary">
Learn more about TUTSTI @ ISWC2024
</Button>
<Button
href="https://iswc2024.semanticweb.org/event/3715c6fc-e2d7-47eb-8c01-5fe4ac589a52/summary"
variant="secondary"
className="md:ml-4"
>
ISWC 2024
<img src={logoISWC.src} class="ms-2 w-6 h-6" />
</Button>
</div>
</section>
</Section>

<Section className="pt-20">
<h2
class="text-3xl font-semibold bg-gradient-to-r from-[#9E0974] to-[#6665E9] inline-block text-transparent bg-clip-text mt-10"
>
Our Approaches, Dataset, Tools and UI
</h2>
<HorizontalTimeline />
</Section>
<HorizontalTimeline />
</Section>

<Section title="" className="pt-20">
<h2
class="text-3xl font-semibold bg-gradient-to-r from-[#9E0974] to-[#6665E9] inline-block text-transparent bg-clip-text mt-10"
>
Our Datasets
</h2>
<div class="flex flex-wrap lg:flex-nowrap mt-8">
<div>
<img
src={mammoth.src}
alt="table illustration"
class="lg:mt-0 lg:col-span-4 max-w-48 object-fit-cover lg:mr-8"
/>
</div>
<div>
<h3 class="mt-2 text-2xl font-semibold text-orange-">Mammotab</h3>
<p class="mb-6 mt-4 md:text-base lg:text-base">
MammoTab is a unique dataset consisting of 1 million Wikipedia
tables, extracted from over 20 million Wikipedia pages, and
annotated using Wikidata. This dataset fills a gap in the current
state-of-the-art resources, making it an excellent tool for testing
and training Semantic Table Interpretation approaches. MammoTab is
specifically designed to address several key challenges, including
disambiguation, homonymy, and NIL-mentions, providing a
comprehensive resource for advancing STI research and applications
</p>
<p class="mt-4 mb-6 md:text-base lg:text-base"></p>
<Button href="/sti-website/mammotab" variant="secondary">
Check out Mammotab
</Button>
<Section title="" className="pt-20">
<h2
class="text-3xl font-semibold bg-gradient-to-r from-[#9E0974] to-[#6665E9] inline-block text-transparent bg-clip-text mt-10"
>
Our Datasets
</h2>
<div class="flex flex-wrap lg:flex-nowrap mt-8">
<div>
<img
src={mammoth.src}
alt="table illustration"
class="lg:mt-0 lg:col-span-4 max-w-48 object-fit-cover lg:mr-8"
/>
</div>
<div>
<h3 class="mt-2 text-2xl font-semibold text-orange-">Mammotab</h3>
<p class="mb-6 mt-4 md:text-base lg:text-base">
MammoTab is a unique dataset consisting of 1 million Wikipedia
tables, extracted from over 20 million Wikipedia pages, and
annotated using Wikidata. This dataset fills a gap in the current
state-of-the-art resources, making it an excellent tool for
testing and training Semantic Table Interpretation approaches.
MammoTab is specifically designed to address several key
challenges, including disambiguation, homonymy, and NIL-mentions,
providing a comprehensive resource for advancing STI research and
applications
</p>
<p class="mt-4 mb-6 md:text-base lg:text-base"></p>
<Button href="/sti-website/mammotab" variant="secondary">
Check out Mammotab
</Button>
</div>
</div>
</div>
</Section>
</Section>
</main>
</Layout>

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