Multi-level Contrastive Learning for Script-based Character Understanding

Abstract

In this work, we tackle the scenario of understanding characters in scripts, which aims to learn the characters' personalities and identities from their utterances. We begin by analyzing several challenges in this scenario, and then propose a multi-level contrastive learning framework to capture characters' global information in a fine-grained manner. To validate the proposed framework, we conduct extensive experiments on three character understanding sub-tasks by comparing with strong pretrained language models, including SpanBERT, Longformer, BigBird and ChatGPT-3.5. Experimental results demonstrate that our method improves the performances by a considerable margin. Through further in-depth analysis, we show the effectiveness of our method in addressing the challenges and provide more hints on the scenario of character understanding. We will open-source our work in this URL. Character Sheldon Jennifer Story Title TBBT The Test Dataset TVSHOWGUESS ROCStories Text Length 528832 41 Character's Related Text Sheldon: " ... we take on Koothrappaliand his dog. Really give ourselves a challenge." Jennifer has a big exam tomorrow. ... Jennifer felt bittersweet about it.