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Benchmarking and implementing Named Entity Recognition (NER) models specifically for extracting structured entities from unstructured financial payment descriptions.
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This project is a comparative study/implementation of standard NLP techniques applied to a specific domain. With 0 stars and no community adoption, it functions primarily as a research artifact. Frontier models now perform zero-shot or few-shot NER on financial data with high accuracy, significantly reducing the unique value of specialized BiLSTM-CRF or BERT-based pipelines for this specific use case.
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