Shypd.aiThe largest open index of AI toolsseqeval is a Python framework for sequence labeling evaluation that assesses the performance of chunking tasks like named-entity recognition and part-of-speech tagging. It supports various evaluation schemes and metrics.
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seqeval is a Python framework designed for the evaluation of sequence labeling tasks, including named-entity recognition (NER), part-of-speech (POS) tagging, and semantic role labeling. It provides robust evaluation capabilities, tested against the industry-standard Perl script `conlleval` for compatibility with CoNLL-2000 shared task data. The framework supports multiple common annotation schemes such as IOB1, IOB2, IOE1, IOE2, IOBES, and BILOU, with strict mode evaluation available for IOBES and BILOU. Users can compute standard metrics like accuracy, precision, recall, and F1 score, and generate comprehensive classification reports to assess model performance effectively. Its flexibility makes it a valuable tool for researchers and developers working on natural language processing tasks.
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