Conference Publishing

Tyler Bikaun

Authors: Tyler Bikaun, Michael Stewart, Wei Liu

2022-05-24

Publication

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

https://aclanthology.org/2022.acl-demo.27/

Quality Indicators

Peer Reviewed

Relevance to the Centre

Acquiring high-quality annotated corpora for complex multi-task information extraction (MT-IE) is an arduous and costly process for human-annotators. Adoption of unsupervised techniques for automated annotation have thus become popular. However, these techniques rely heavily on dictionaries, gazetteers, and knowledge bases. While such resources are abundant for general domains, they are scarce for specialised technical domains. To tackle this challenge, we present QuickGraph, the first collaborative MT-IE annotation tool built with indirect weak supervision and clustering to maximise annotator productivity.QuickGraph's main contribution is a set of novel features that enable knowledge graph extraction through rapid and consistent complex multi-task entity and relation annotation. In this paper, we discuss these key features and qualitatively compare QuickGraph to existing annotation tools.

DOI: Not available

Link to Publication