A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit <a rel="external noopener" href="https://arxiv.org/pdf/1907.00854v2.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
Katecheo: A Portable and Modular System for Multi-Topic Question Answering
[article]
<span title="2020-01-31">2020</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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<span title="2019-07-01">2019</span>
<span class="release-stage" >pre-print</span>
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1907.00854v1">arXiv:1907.00854v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/npqe6rdukjgwjesev5xkmu2lgq">fatcat:npqe6rdukjgwjesev5xkmu2lgq</a> </span>
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1907.00854v1">arXiv:1907.00854v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/npqe6rdukjgwjesev5xkmu2lgq">fatcat:npqe6rdukjgwjesev5xkmu2lgq</a> </span>
We introduce a modular system that can be deployed on any Kubernetes cluster for question answering via REST API. This system, called Katecheo, includes three configurable modules that collectively enable identification of questions, classification of those questions into topics, document search, and reading comprehension. We demonstrate the system using publicly available knowledge base articles extracted from Stack Exchange sites. However, users can extend the system to any number of topics,
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<a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1907.00854v2">arXiv:1907.00854v2</a>
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... r domains, without the need to modify any of the model serving code or train their own models. All components of the system are open source and available under a permissive Apache 2 License.
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