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    <titleInfo>
        <title>Constraint-Based Question Answering with Knowledge Graph</title>
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    <name type="personal">
        <namePart type="given">Junwei</namePart>
        <namePart type="family">Bao</namePart>
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    <name type="personal">
        <namePart type="given">Nan</namePart>
        <namePart type="family">Duan</namePart>
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    <name type="personal">
        <namePart type="given">Zhao</namePart>
        <namePart type="family">Yan</namePart>
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    <name type="personal">
        <namePart type="given">Ming</namePart>
        <namePart type="family">Zhou</namePart>
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    <name type="personal">
        <namePart type="given">Tiejun</namePart>
        <namePart type="family">Zhao</namePart>
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            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
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            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
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            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
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            <publisher>The COLING 2016 Organizing Committee</publisher>
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    <abstract>WebQuestions and SimpleQuestions are two benchmark data-sets commonly used in recent knowledge-based question answering (KBQA) work. Most questions in them are ‘simple’ questions which can be answered based on a single relation in the knowledge base. Such data-sets lack the capability of evaluating KBQA systems on complicated questions. Motivated by this issue, we release a new data-set, namely ComplexQuestions, aiming to measure the quality of KBQA systems on ‘multi-constraint’ questions which require multiple knowledge base relations to get the answer. Beside, we propose a novel systematic KBQA approach to solve multi-constraint questions. Compared to state-of-the-art methods, our approach not only obtains comparable results on the two existing benchmark data-sets, but also achieves significant improvements on the ComplexQuestions.</abstract>
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        <url>https://aclanthology.org/C16-1236</url>
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        <date>2016-12</date>
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%0 Conference Proceedings
%T Constraint-Based Question Answering with Knowledge Graph
%A Bao, Junwei
%A Duan, Nan
%A Yan, Zhao
%A Zhou, Ming
%A Zhao, Tiejun
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F bao-etal-2016-constraint
%X WebQuestions and SimpleQuestions are two benchmark data-sets commonly used in recent knowledge-based question answering (KBQA) work. Most questions in them are ‘simple’ questions which can be answered based on a single relation in the knowledge base. Such data-sets lack the capability of evaluating KBQA systems on complicated questions. Motivated by this issue, we release a new data-set, namely ComplexQuestions, aiming to measure the quality of KBQA systems on ‘multi-constraint’ questions which require multiple knowledge base relations to get the answer. Beside, we propose a novel systematic KBQA approach to solve multi-constraint questions. Compared to state-of-the-art methods, our approach not only obtains comparable results on the two existing benchmark data-sets, but also achieves significant improvements on the ComplexQuestions.
%U https://aclanthology.org/C16-1236
%P 2503-2514

Markdown (Informal)

[Constraint-Based Question Answering with Knowledge Graph](https://aclanthology.org/C16-1236) (Bao et al., COLING 2016)

• Constraint-Based Question Answering with Knowledge Graph (Bao et al., COLING 2016)

ACL

• Junwei Bao, Nan Duan, Zhao Yan, Ming Zhou, and Tiejun Zhao. 2016. Constraint-Based Question Answering with Knowledge Graph. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2503–2514, Osaka, Japan. The COLING 2016 Organizing Committee.