Character Identification on Multiparty Conversation: Identifying Mentions of Characters in TV Shows

This paper introduces a subtask of entity linking, called character identification, that maps mentions in multiparty conversation to their referent characters. Transcripts of TV shows are collected as the sources of our corpus and automatically annotated with mentions by linguistically-motivated rules. These mentions are manually linked to their referents through crowdsourcing. Our corpus comprises 543 scenes from two TV shows, and shows the inter-annotator agreement of κ = 79.96. For statistical modeling, this task is reformulated as coreference resolution, and experimented with a state-of-the-art system on our corpus. Our best model gives a purity score of 69.21 on average, which is promising given the challenging nature of this task and our corpus.