@inproceedings{yu-etal-2022-mic,
title = "{MIC}: A Multi-task Interactive Curation Tool",
author = "Yu, Shi and
Yang, Mingfeng and
Parker, Jerrod and
Brock, Stephen",
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.22",
doi = "10.18653/v1/2022.emnlp-demos.22",
pages = "224--231",
abstract = "This paper introduces MIC, a Multi-task Interactive Curation tool, a human-machine collaborative curation tool for multiple NLP tasks. The tool aims to borrow recent advances in literature to solve pain-points in real NLP tasks. Firstly, it supports multiple projects with multiple users which enables collaborative annotations. Secondly, MIC allows easy integration of pre-trained models, rules, and dictionaries to auto label the text and speed up the labeling process. Thirdly, MIC supports annotation at different scales (span of characters and words, tokens and lines, or document) and different types (free text, sentence labels, entity labels, and relationship triplets) with easy GUI operations.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="yu-etal-2022-mic">
<titleInfo>
<title>MIC: A Multi-task Interactive Curation Tool</title>
</titleInfo>
<name type="personal">
<namePart type="given">Shi</namePart>
<namePart type="family">Yu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mingfeng</namePart>
<namePart type="family">Yang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jerrod</namePart>
<namePart type="family">Parker</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Stephen</namePart>
<namePart type="family">Brock</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>This paper introduces MIC, a Multi-task Interactive Curation tool, a human-machine collaborative curation tool for multiple NLP tasks. The tool aims to borrow recent advances in literature to solve pain-points in real NLP tasks. Firstly, it supports multiple projects with multiple users which enables collaborative annotations. Secondly, MIC allows easy integration of pre-trained models, rules, and dictionaries to auto label the text and speed up the labeling process. Thirdly, MIC supports annotation at different scales (span of characters and words, tokens and lines, or document) and different types (free text, sentence labels, entity labels, and relationship triplets) with easy GUI operations.</abstract>
<identifier type="citekey">yu-etal-2022-mic</identifier>
<identifier type="doi">10.18653/v1/2022.emnlp-demos.22</identifier>
<location>
<url>https://aclanthology.org/2022.emnlp-demos.22</url>
</location>
<part>
<date>2022-12</date>
<extent unit="page">
<start>224</start>
<end>231</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T MIC: A Multi-task Interactive Curation Tool
%A Yu, Shi
%A Yang, Mingfeng
%A Parker, Jerrod
%A Brock, Stephen
%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 yu-etal-2022-mic
%X This paper introduces MIC, a Multi-task Interactive Curation tool, a human-machine collaborative curation tool for multiple NLP tasks. The tool aims to borrow recent advances in literature to solve pain-points in real NLP tasks. Firstly, it supports multiple projects with multiple users which enables collaborative annotations. Secondly, MIC allows easy integration of pre-trained models, rules, and dictionaries to auto label the text and speed up the labeling process. Thirdly, MIC supports annotation at different scales (span of characters and words, tokens and lines, or document) and different types (free text, sentence labels, entity labels, and relationship triplets) with easy GUI operations.
%R 10.18653/v1/2022.emnlp-demos.22
%U https://aclanthology.org/2022.emnlp-demos.22
%U https://doi.org/10.18653/v1/2022.emnlp-demos.22
%P 224-231
Markdown (Informal)
[MIC: A Multi-task Interactive Curation Tool](https://aclanthology.org/2022.emnlp-demos.22) (Yu et al., EMNLP 2022)
ACL
- Shi Yu, Mingfeng Yang, Jerrod Parker, and Stephen Brock. 2022. MIC: A Multi-task Interactive Curation Tool. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 224–231, Abu Dhabi, UAE. Association for Computational Linguistics.