A Joint Model for Quotation Attribution and Coreference Resolution

We address the problem of automatically attributing quotations to speakers, which has great relevance in text mining and media monitoring applications. While current systems report high accuracies for this task, they either work at mentionlevel (getting credit for detecting uninformative mentions such as pronouns), or assume the coreferent mentions have been detected beforehand; the inaccuracies in this preprocessing step may lead to error propagation. In this paper, we introduce a joint model for entity-level quotation attribution and coreference resolution, exploiting correlations between the two tasks. We design an evaluation metric for attribution that captures all speakers’ mentions. We present results showing that both tasks benefit from being treated jointly.