Human in the Loop

This paper tests whether large language models can extend lexical knowledge bases. Human evaluators accepted 86.7% of novel concepts. Automatic overlap metrics missed many valid additions.

This paper explores the concept of basicness in language through attention-based neural networks and human-in-the-loop methodology. Based on the Master’s thesis work.