Temporal Knowledge Graph Construction from Text
| Project/Area Number |
21K17816
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 61030:Intelligent informatics-related
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| Research Institution | Japan Advanced Institute of Science and Technology |
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Principal Investigator |
K. Natthawut 北陸先端科学技術大学院大学, 先端科学技術研究科, 講師 (40818100)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2022: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2021: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | Knowledge Graph / Knowledge Acquisition / 金融 / Temporal Knowledge Graph / Knowledge Extraction / Financial Report / Financial Application / Knowledge Representation / Relation Extraction / Event Extraction |
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| Outline of Research at the Start |
Knowledge Graph plays a key role in various artificial intelligence applications. Generally, a knowledge graph is built to express static knowledge. Nevertheless, knowledge usually changes over time. A knowledge graph without considering the time does not satisfy the change. Therefore, this project aims to study a temporal knowledge graph and to develop a novel framework for constructing temporal knowledge graphs from text. The outcomes of this research will expand the study on the knowledge graph area and facilitate the time-aware knowledge graph-based applications.
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| Outline of Annual Research Achievements |
This research aims to construct a temporal knowledge graph from textual data. In this fiscal year, we developed FinKG-JP, a temporal Japanese knowledge graph in the financial domain, using annual reports provided by the Financial Services Agency via EDINET. Temporal information, including details from the reports and stock prices, was extracted using our financial ontology as a template. This temporal information is encoded at the edges of the knowledge graph. For the ontology in FinKG-JP, we derived concepts from FinKG and added concepts specific to the Japanese market. Overall, FinKG-JP contains more than 5 million entities.
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Report
(3 results)
Research Products
(8 results)
