BridgeNLP serves as a universal adapter layer between advanced NLP models (e.g., AllenNLP, Hugging Face) and structured token pipelines (e.g., spaCy). Its core goal is to allow developers to integrate models like coreference resolution, semantic role labeling, or named entity recognition into token-based applications in a clean, aligned, and memory-safe manner.
BridgeNLP serves as a universal adapter layer between advanced NLP models (e.g., AllenNLP, Hugging Face) and structured token pipelines (e.g., spaCy). Its core goal is to allow developers to integrate models like coreference resolution, semantic role labeling, or named entity recognition into token-based applications in a clean, aligned, and memory-safe manner.