Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: VANiLLa : Verbalized Answers in Natural Language at Large Scale   In the last years, there have been significant developments in the area of
Question Answering over Knowledge Graphs (KGQA). Despite all the notable
advancements, current KGQA datasets only provide the answers as the direct
output result of the formal query, rather than full sentences incorporating
question context. For achieving coherent answers sentence with the question's
vocabulary, template-based verbalization so are usually employed for a better
representation of answers, which in turn require extensive expert intervention.
Thus, making way for machine learning approaches; however, there is a scarcity
of datasets that empower machine learning models in this area. Hence, we
provide the VANiLLa dataset which aims at reducing this gap by offering answers
in natural language sentences. The answer sentences in this dataset are
syntactically and semantically closer to the question than to the triple fact.
Our dataset consists of over 100k simple questions adapted from the CSQA and
SimpleQuestionsWikidata datasets and generated using a semi-automatic
framework. We also present results of training our dataset on multiple baseline
models adapted from current state-of-the-art Natural Language Generation (NLG)
architectures. We believe that this dataset will allow researchers to focus on
finding suitable methodologies and architectures for answer verbalization.

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The categories of this paper are: comp-gas
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The categories of this paper are: math
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The categories of this paper are: stat
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The categories of this paper are: chao-dyn
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The categories of this paper are: alg-geom
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The categories of this paper are: eess
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The categories of this paper are: patt-sol
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The categories of this paper are: funct-an
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The categories of this paper are: solv-int
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The categories of this paper are: mtrl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: supr-con
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The categories of this paper are: nlin
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The categories of this paper are: astro-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-ex