Rethinking Annotation: Can Language Learners Contribute?

TL;DR

This study explores whether language learners can effectively contribute to dataset annotation, especially for under-resourced languages, and finds that intermediate and advanced learners can provide accurate labels with additional resources, also aiding their language proficiency.

Contribution

It demonstrates that language learners can be viable annotators for NLP datasets, expanding annotation possibilities for less-resourced languages.

Findings

Learners with intermediate or advanced proficiency provide accurate labels.

Additional resources like dictionaries improve annotation quality.

Annotation activities enhance learners' vocabulary and grammar.

Abstract

Researchers have traditionally recruited native speakers to provide annotations for widely used benchmark datasets. However, there are languages for which recruiting native speakers can be difficult, and it would help to find learners of those languages to annotate the data. In this paper, we investigate whether language learners can contribute annotations to benchmark datasets. In a carefully controlled annotation experiment, we recruit 36 language learners, provide two types of additional resources (dictionaries and machine-translated sentences), and perform mini-tests to measure their language proficiency. We target three languages, English, Korean, and Indonesian, and the four NLP tasks of sentiment analysis, natural language inference, named entity recognition, and machine reading comprehension. We find that language learners, especially those with intermediate or advanced levels of language proficiency, are able to provide fairly accurate labels with the help of additional resources. Moreover, we show that data annotation improves learners' language proficiency in terms of vocabulary and grammar. One implication of our findings is that broadening the annotation task to include language learners can open up the opportunity to build benchmark datasets for languages for which it is difficult to recruit native speakers.