The Impresso NER model is a multilingual named entity recognition model specifically designed for historical document processing. Based on the stacked Transformer architecture, it can identify fine-grained and coarse-grained entity types in digitized historical texts, including person names, titles, locations, etc. The model is optimized for OCR noise, spelling variations, and non-standard language usage in historical documents.
Natural Language Processing
TransformersMultiple Languages