@inproceedings{shnarch-etal-2022-label,
title = "Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours",
author = "Shnarch, Eyal and
Halfon, Alon and
Gera, Ariel and
Danilevsky, Marina and
Katsis, Yannis and
Choshen, Leshem and
Santillan Cooper, Martin and
Epelboim, Dina and
Zhang, Zheng and
Wang, Dakuo and
Yip, Lucy and
Ein-Dor, Liat and
Dankin, Lena and
Shnayderman, Ilya and
Aharonov, Ranit and
Li, Yunyao and
Liberman, Naftali and
Levin Slesarev, Philip and
Newton, Gwilym and
Ofek-Koifman, Shila and
Slonim, Noam and
Katz, Yoav",
editor = "Che, Wanxiang and
Shutova, Ekaterina",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = dec,
year = "2022",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-demos.16/",
doi = "10.18653/v1/2022.emnlp-demos.16",
pages = "159--168",
abstract = "Label Sleuth is an open source platform for building text classifiers which does not require coding skills nor machine learning knowledge.- Project website: [\url{https://www.label-sleuth.org/}](\url{https://www.label-sleuth.org/})- Link to screencast video: [\url{https://vimeo.com/735675461}](\url{https://vimeo.com/735675461}){\#}{\#}{\#} AbstractText classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a classifier generally requires coding skills and ML knowledge, which poses a significant barrier for many potential users. To lift this barrier we introduce *Label Sleuth*, a free open source system for labeling and creating text classifiers. This system is unique for: - being a no-code system, making NLP accessible for non-experts. - guiding its users throughout the entire labeling process until they obtain their desired classifier, making the process efficient - from cold start to a classifier in a few hours. - being open for configuration and extension by developers. By open sourcing Label Sleuth we hope to build a community of users and developers that will widen the utilization of NLP models."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="shnarch-etal-2022-label">
<titleInfo>
<title>Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours</title>
</titleInfo>
<name type="personal">
<namePart type="given">Eyal</namePart>
<namePart type="family">Shnarch</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alon</namePart>
<namePart type="family">Halfon</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ariel</namePart>
<namePart type="family">Gera</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marina</namePart>
<namePart type="family">Danilevsky</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Yannis</namePart>
<namePart type="family">Katsis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Leshem</namePart>
<namePart type="family">Choshen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Martin</namePart>
<namePart type="family">Santillan Cooper</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dina</namePart>
<namePart type="family">Epelboim</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Zheng</namePart>
<namePart type="family">Zhang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dakuo</namePart>
<namePart type="family">Wang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lucy</namePart>
<namePart type="family">Yip</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Liat</namePart>
<namePart type="family">Ein-Dor</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lena</namePart>
<namePart type="family">Dankin</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ilya</namePart>
<namePart type="family">Shnayderman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ranit</namePart>
<namePart type="family">Aharonov</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Yunyao</namePart>
<namePart type="family">Li</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Naftali</namePart>
<namePart type="family">Liberman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Philip</namePart>
<namePart type="family">Levin Slesarev</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Gwilym</namePart>
<namePart type="family">Newton</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Shila</namePart>
<namePart type="family">Ofek-Koifman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Noam</namePart>
<namePart type="family">Slonim</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Yoav</namePart>
<namePart type="family">Katz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2022-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations</title>
</titleInfo>
<name type="personal">
<namePart type="given">Wanxiang</namePart>
<namePart type="family">Che</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ekaterina</namePart>
<namePart type="family">Shutova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Abu Dhabi, UAE</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Label Sleuth is an open source platform for building text classifiers which does not require coding skills nor machine learning knowledge.- Project website: [https://www.label-sleuth.org/](https://www.label-sleuth.org/)- Link to screencast video: [https://vimeo.com/735675461](https://vimeo.com/735675461)### AbstractText classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a classifier generally requires coding skills and ML knowledge, which poses a significant barrier for many potential users. To lift this barrier we introduce *Label Sleuth*, a free open source system for labeling and creating text classifiers. This system is unique for: - being a no-code system, making NLP accessible for non-experts. - guiding its users throughout the entire labeling process until they obtain their desired classifier, making the process efficient - from cold start to a classifier in a few hours. - being open for configuration and extension by developers. By open sourcing Label Sleuth we hope to build a community of users and developers that will widen the utilization of NLP models.</abstract>
<identifier type="citekey">shnarch-etal-2022-label</identifier>
<identifier type="doi">10.18653/v1/2022.emnlp-demos.16</identifier>
<location>
<url>https://aclanthology.org/2022.emnlp-demos.16/</url>
</location>
<part>
<date>2022-12</date>
<extent unit="page">
<start>159</start>
<end>168</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours
%A Shnarch, Eyal
%A Halfon, Alon
%A Gera, Ariel
%A Danilevsky, Marina
%A Katsis, Yannis
%A Choshen, Leshem
%A Santillan Cooper, Martin
%A Epelboim, Dina
%A Zhang, Zheng
%A Wang, Dakuo
%A Yip, Lucy
%A Ein-Dor, Liat
%A Dankin, Lena
%A Shnayderman, Ilya
%A Aharonov, Ranit
%A Li, Yunyao
%A Liberman, Naftali
%A Levin Slesarev, Philip
%A Newton, Gwilym
%A Ofek-Koifman, Shila
%A Slonim, Noam
%A Katz, Yoav
%Y Che, Wanxiang
%Y Shutova, Ekaterina
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F shnarch-etal-2022-label
%X Label Sleuth is an open source platform for building text classifiers which does not require coding skills nor machine learning knowledge.- Project website: [https://www.label-sleuth.org/](https://www.label-sleuth.org/)- Link to screencast video: [https://vimeo.com/735675461](https://vimeo.com/735675461)### AbstractText classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a classifier generally requires coding skills and ML knowledge, which poses a significant barrier for many potential users. To lift this barrier we introduce *Label Sleuth*, a free open source system for labeling and creating text classifiers. This system is unique for: - being a no-code system, making NLP accessible for non-experts. - guiding its users throughout the entire labeling process until they obtain their desired classifier, making the process efficient - from cold start to a classifier in a few hours. - being open for configuration and extension by developers. By open sourcing Label Sleuth we hope to build a community of users and developers that will widen the utilization of NLP models.
%R 10.18653/v1/2022.emnlp-demos.16
%U https://aclanthology.org/2022.emnlp-demos.16/
%U https://doi.org/10.18653/v1/2022.emnlp-demos.16
%P 159-168
Markdown (Informal)
[Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours](https://aclanthology.org/2022.emnlp-demos.16/) (Shnarch et al., EMNLP 2022)
ACL
- Eyal Shnarch, Alon Halfon, Ariel Gera, Marina Danilevsky, Yannis Katsis, Leshem Choshen, Martin Santillan Cooper, Dina Epelboim, Zheng Zhang, Dakuo Wang, Lucy Yip, Liat Ein-Dor, Lena Dankin, Ilya Shnayderman, Ranit Aharonov, Yunyao Li, Naftali Liberman, Philip Levin Slesarev, Gwilym Newton, Shila Ofek-Koifman, Noam Slonim, and Yoav Katz. 2022. Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 159–168, Abu Dhabi, UAE. Association for Computational Linguistics.