In the context of financial information explosion, unstructured text (such as market news, corporate financial reports, etc.) contains key event information, and event extraction technology becomes the core bridge for quantitative analysis through structured "who, when, where, and what" elements. However, traditional methods face three major challenges: syntactic complexity, dynamic evolution of terminology, and intertwining of multiple event entities. Existing research has limitations such as inconsistent standards, ineffective cross sentence causal capture, and dependence on annotated data. This study proposes a document level financial event extraction method based on dependency syntax enhancement and BKP algorithm optimization: integrating syntactic dependency relationships and part of speech/entity type information through graph attention networks to enhance the semantic integrity of argument extraction; Using RoBERTa to capture document level context, combined with importance score optimization and dynamic pruning strategy, to achieve efficient combination decoding and reduce redundant computation. Empirical evidence on the publicly available CFA dataset shows that the new model significantly outperforms existing benchmarks in terms of accuracy (improved by 8% -12%) and processing speed (improved by 30% -50%), especially in multi event text scenarios. Research has found that the syntactic semantic enhancement module effectively solves the problem of extracting semantic integrity from complex causal sentences. The BKP algorithm reduces the complexity of multi event decoding through path optimization and dynamic pruning, while maintaining a high recall rate. This study achieved semantic coherence from sentence level to document level, providing a new paradigm for dynamic information extraction in financial scenarios. In the future, the model will be extended to non-financial fields for generalization verification, and visualization tools will be developed to enhance interpretability.

Wei Sun. Research on Financial Document Event Extraction Method Based on Dependency Syntax Enhancement and BKP Algorithm Optimization. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 1: 105-114. https://doi.doi.org/10.3807/IJSSEM.2026.070112.

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