Maya Kruse
2023
Improving NER Research Workflows with SeqScore
Constantine Lignos
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Maya Kruse
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Andrew Rueda
Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023)
We describe the features of SeqScore, an MIT-licensed Python toolkit for working with named entity recognition (NER) data.While SeqScore began as a tool for NER scoring, it has been expanded to help with the full lifecycle of working with NER data: validating annotation, providing at-a-glance and detailed summaries of the data, modifying annotation to support experiments, scoring system output, and aiding with error analysis.SeqScore is released via PyPI (https://pypi.org/project/seqscore/) and development occurs on GitHub (https://github.com/bltlab/seqscore).
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