Techniques like logical consequence allow causal relations to be used in niche practical applications such as event prediction which is useful for diverse domains such as security and finance. A cause and effect relationship is stronger than a correlation between events, and therefore aggregated causal relations extracted from large corpora can be used in numerous applications such as question-answering and summarisation to produce superior results than traditional approaches. Causation in the written form can be referred to as a causal relation where a cause event entails the occurrence of an effect event. Causationin written natural language can express a strong relationship between events and facts.
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