Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Question Answering over Knowledge Graphs via Structural Query Patterns   Natural language question answering over knowledge graphs is an important and
interesting task as it enables common users to gain accurate answers in an easy
and intuitive manner. However, it remains a challenge to bridge the gap between
unstructured questions and structured knowledge graphs. To address the problem,
a natural discipline is building a structured query to represent the input
question. Searching the structured query over the knowledge graph can produce
answers to the question. Distinct from the existing methods that are based on
semantic parsing or templates, we propose an effective approach powered by a
novel notion, structural query pattern, in this paper. Given an input question,
we first generate its query sketch that is compatible with the underlying
structure of the knowledge graph. Then, we complete the query graph by labeling
the nodes and edges under the guidance of the structural query pattern.
Finally, answers can be retrieved by executing the constructed query graph over
the knowledge graph. Evaluations on three question answering benchmarks show
that our proposed approach outperforms state-of-the-art methods significantly.

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The categories of this paper are: mtrl-th
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The categories of this paper are: acc-phys
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The categories of this paper are: bayes-an
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The categories of this paper are: eess
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The categories of this paper are: dg-ga
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The categories of this paper are: quant-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci
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The categories of this paper are: math
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The categories of this paper are: plasm-ph
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The categories of this paper are: q-fin
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The categories of this paper are: q-alg
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The categories of this paper are: hep-ex
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The categories of this paper are: alg-geom
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The categories of this paper are: cmp-lg
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The categories of this paper are: chem-ph