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        <title>SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation</title>
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    <name type="personal">
        <namePart type="given">Chester</namePart>
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    <name type="personal">
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    <name type="personal">
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            <namePart type="given">Marina</namePart>
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    <abstract>To address a looming crisis of unreproducible evaluation for named entity recognition, we propose guidelines and introduce SeqScore, a software package to improve reproducibility. The guidelines we propose are extremely simple and center around transparency regarding how chunks are encoded and scored. We demonstrate that despite the apparent simplicity of NER evaluation, unreported differences in the scoring procedure can result in changes to scores that are both of noticeable magnitude and statistically significant. We describe SeqScore, which addresses many of the issues that cause replication failures.</abstract>
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    <identifier type="doi">10.18653/v1/2021.eval4nlp-1.5</identifier>
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%0 Conference Proceedings
%T SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation
%A Palen-Michel, Chester
%A Holley, Nolan
%A Lignos, Constantine
%Y Gao, Yang
%Y Eger, Steffen
%Y Zhao, Wei
%Y Lertvittayakumjorn, Piyawat
%Y Fomicheva, Marina
%S Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F palen-michel-etal-2021-seqscore
%X To address a looming crisis of unreproducible evaluation for named entity recognition, we propose guidelines and introduce SeqScore, a software package to improve reproducibility. The guidelines we propose are extremely simple and center around transparency regarding how chunks are encoded and scored. We demonstrate that despite the apparent simplicity of NER evaluation, unreported differences in the scoring procedure can result in changes to scores that are both of noticeable magnitude and statistically significant. We describe SeqScore, which addresses many of the issues that cause replication failures.
%R 10.18653/v1/2021.eval4nlp-1.5
%U https://aclanthology.org/2021.eval4nlp-1.5
%U https://doi.org/10.18653/v1/2021.eval4nlp-1.5
%P 40-50

Markdown (Informal)

[SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation](https://aclanthology.org/2021.eval4nlp-1.5) (Palen-Michel et al., Eval4NLP 2021)

• SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation (Palen-Michel et al., Eval4NLP 2021)

ACL

• Chester Palen-Michel, Nolan Holley, and Constantine Lignos. 2021. SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation. In Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems, pages 40–50, Punta Cana, Dominican Republic. Association for Computational Linguistics.