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    <titleInfo>
        <title>iobes: Library for Span Level Processing</title>
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    <name type="personal">
        <namePart type="given">Brian</namePart>
        <namePart type="family">Lester</namePart>
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        <dateIssued>2020-nov</dateIssued>
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            <title>Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS)</title>
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            <publisher>Association for Computational Linguistics</publisher>
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    <abstract>Many tasks in natural language processing, such as named entity recognition and slot-filling, involve identifying and labeling specific spans of text. In order to leverage common models, these tasks are often recast as sequence labeling tasks. Each token is given a label and these labels are prefixed with special tokens such as B- or I-. After a model assigns labels to each token, these prefixes are used to group the tokens into spans. Properly parsing these annotations is critical for producing fair and comparable metrics; however, despite its importance, there is not an easy-to-use, standardized, programmatically integratable library to help work with span labeling. To remedy this, we introduce our open-source library, iobes. iobes is used for parsing, converting, and processing spans represented as token level decisions.</abstract>
    <identifier type="citekey">lester-2020-iobes</identifier>
    <identifier type="doi">10.18653/v1/2020.nlposs-1.16</identifier>
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        <url>https://aclanthology.org/2020.nlposs-1.16</url>
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        <date>2020-nov</date>
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            <start>115</start>
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%0 Conference Proceedings
%T iobes: Library for Span Level Processing
%A Lester, Brian
%S Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS)
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F lester-2020-iobes
%X Many tasks in natural language processing, such as named entity recognition and slot-filling, involve identifying and labeling specific spans of text. In order to leverage common models, these tasks are often recast as sequence labeling tasks. Each token is given a label and these labels are prefixed with special tokens such as B- or I-. After a model assigns labels to each token, these prefixes are used to group the tokens into spans. Properly parsing these annotations is critical for producing fair and comparable metrics; however, despite its importance, there is not an easy-to-use, standardized, programmatically integratable library to help work with span labeling. To remedy this, we introduce our open-source library, iobes. iobes is used for parsing, converting, and processing spans represented as token level decisions.
%R 10.18653/v1/2020.nlposs-1.16
%U https://aclanthology.org/2020.nlposs-1.16
%U https://doi.org/10.18653/v1/2020.nlposs-1.16
%P 115-119

Markdown (Informal)

[iobes: Library for Span Level Processing](https://aclanthology.org/2020.nlposs-1.16) (Lester, NLPOSS 2020)

• iobes: Library for Span Level Processing (Lester, NLPOSS 2020)

ACL

• Brian Lester. 2020. iobes: Library for Span Level Processing. In Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS), pages 115–119, Online. Association for Computational Linguistics.