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| Knowledge Element Logical Relation Extraction Method |
| Cheng Wei1, Zheng Dejun1, Zhu Mengdie2, Cong Tianshi1, Wang Yanhong2 |
1.College of Information Management, Nanjing Agricultural University, Nanjing 210095
2.School of Information Management, Nanjing University, Nanjing 210023 |
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Abstract The extraction of knowledge element logical relation focuses on the syntactic structure and syntactic features of the context and realizes context-scoped relation extraction by defining trigger word rules through contextual functional semantic dependencies. To eliminate the structural limitation of context, this study proposes a new method for the extraction of knowledge element logical relation. First, based on the domain literature, the knowledge element collection is constructed through knowledge element extraction. Second, based on the domain knowledge characteristics, a knowledge element attribute description framework is constructed to provide an all-round and fine-grained unified description of knowledge elements, and the knowledge element attribute collection is constructed based on knowledge element attribute extraction. Finally, the logical relation types are defined in accordance with the actual needs. Through logical relation instance analysis and attribute comparative relation analysis, the logical relation rule base is constructed via characterization and summarization. This is done by taking the basic relations, such as co-occurrence, inclusion, and correlation of attribute values, as clues, and the logical relation extraction is realized through rule matching. Considering the South China Sea rights protection evidence knowledge element, some evidence from different text sources are selected, and the types of logical relations between evidence and their extraction rules are defined. Based on the extraction of knowledge elements and their attributes, the logical relation extraction between the South China Sea rights protection evidence of juxtaposition, succession, rebuttal, and reinforcement is realized based on rule matching, and the logical relation mapping of the South China Sea rights protection evidence is constructed. The feasibility of the proposed method is empirically verified, which can provide new ideas for research on the logical relation extraction of knowledge elements.
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Received: 04 August 2023
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