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.- Anthology ID:
- 2022.emnlp-demos.22
- Volume:
- Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, UAE
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 224–231
- Language:
- URL:
- https://aclanthology.org/2022.emnlp-demos.22
- DOI:
- 10.18653/v1/2022.emnlp-demos.22
- Cite (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.
- Cite (Informal):
- MIC: A Multi-task Interactive Curation Tool (Yu et al., EMNLP 2022)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2022.emnlp-demos.22.pdf