Báo cáo khoa học: "Learning Script Knowledge with Web Experiments"
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We describe a novel approach to unsupervised learning of the events that make up a script, along with constraints on their temporal ordering. We collect naturallanguage descriptions of script-specific event sequences from volunteers over the Internet. Then we compute a graph representation of the script’s temporal structure using a multiple sequence alignment algorithm. The evaluation of our system shows that we outperform two informed baselines.
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