A text relation extraction method that combines multi-level information extraction and noise reduction
A technology of relation extraction and information extraction, applied in relational databases, neural learning methods, instruments, etc., can solve problems such as low F1 value, and achieve the effect of reducing impact, solving identification difficulties, and improving evaluation indicators
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[0065] The specific process of a text relation extraction method that integrates multi-level information extraction and noise reduction is as follows: figure 1 shown. This embodiment describes the flow and overall framework of the method of the present invention, respectively as follows figure 1 and figure 2 shown. During specific implementation, the method of the present invention can be applied to extract triple information in the text data, and update the knowledge of the knowledge graph. The reason why textual relation extraction is important is because the existing structured knowledge accounts for a small proportion of the existing knowledge, and the real-world knowledge usually exists in the form of texts, and it is still growing rapidly. Manually constructing structured knowledge requires a lot of time and money, and it is difficult for manual methods to keep up with the speed of knowledge growth.
[0066] The data used in this example comes from the DocRED datase...
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