In this paper, we present a formalization of the task of parsing movie screenplays. While researchers have previously motivated the need for parsing movie screenplays, to the best of our knowledge, there is no work that has presented an evaluation for the task. Moreover, all the approaches in the literature thus far have been regular expression based. In this paper, we present an NLP and ML based approach to the task, and show that this approach outperforms the regular expression based approach by a large and statistically significant margin. One of the main challenges we faced early on was the absence of training and test data. We propose a methodology for using well structured screenplays to create training data for anticipated anomalies in the structure of screenplays.
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