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Legal Entity Extraction using a Pointer Generator Network
To overcome the challenges of our noisy training data, e. g., text extraction errors and/or typos and unknown label indices, we frame the NER task as a sequence generation task (seq2seq) and train a pointer generator network to generate the entities in the document rather than label them.
Named Entity Recognition in the Legal Domain using a Pointer Generator Network
Named Entity Recognition (NER) is the task of identifying and classifying named entities in unstructured text.
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