Grounding text and knowledge base by using distributed representation and their compositions
| Project/Area Number |
15H05318
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| Research Category |
Grant-in-Aid for Young Scientists (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Tokyo Institute of Technology (2017)
Tohoku University (2015-2016) |
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Principal Investigator |
Okazaki Naoaki 東京工業大学, 情報理工学院, 教授 (50601118)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥16,510,000 (Direct Cost: ¥12,700,000、Indirect Cost: ¥3,810,000)
Fiscal Year 2017: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2016: ¥7,020,000 (Direct Cost: ¥5,400,000、Indirect Cost: ¥1,620,000)
Fiscal Year 2015: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
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| Keywords | 自然言語処理 / 人工知能 / 深層学習 / 分散表現 / 知識ベース / 知識獲得 / 意味解析 / 表現学習 / 意見分析 / 質問応答 / 知能情報学 / 言語資源 |
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| Outline of Final Research Achievements |
In order to realize computers that can understand and infer on natural languages, a mechanism for collecting and utilizing the commonsense knowledge is essential. We need address three research topics, acquisition of a large-scale knowledge base, grounding a text with the knowledge base, and an inference method on the grounded text. In this project, we built corpora where a text is grounded on instances of a knowledge base. In order to associate relational patterns into a knowledge base, we proposed a novel method for composing a vector of a relation pattern from its constituent words and for disambiguating the sense of a relation pattern. We demonstrated the effectiveness of these studies not only by the experiments on individual tasks but also by applying downstream tasks such as question answering and stance detection.
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Report
(4 results)
Research Products
(54 results)
