A Review of Generative Methods for Extracting Relational Triples from Natural Language Texts
摘要
The paper discusses modern approaches for extracting relational triples from natural language texts based on sequence transformation technology. The authors have identified and structured existing solutions into a set of groups of methods: classical methods for converting sequences, methods for converting sequences into a set, and prompt methods. A comparative analysis of the advantages and disadvantages of these methods is performed.