GPTs Are Multilingual Annotators for Sequence Generation Tasks

Understand

Data annotation is an essential step for constructing new datasets.

• However, the conventional approach of data annotation through crowdsourcing is both time-consuming and expensive.
• In addition, the complexity of this process increases when dealing with low-resource languages owing to the difference in the language pool of crowdworkers.
• To address these issues, this study proposes an autonomous annotation method by utilizing large language models, which have been recently demonstrated to exhibit remarkable performance.