Finding the Causality of an Event in News Articles

Abstract

This paper discusses about the finding of causality of an event in newspaper articles. The analysis of causality , otherwise known as cause and effect is crucial for building efficient Natural Language Understanding (NLU) supported AI systems such as Event tracking and it is considered as a complex semantic relation under discourse theory. A cause-effect relation consists of a linguistic marker and its two arguments. The arguments are semantic arguments where the cause is the first argument (Arg1) and the effect is the second argument(Arg2). In this work we have considered the causal relations in Tamil Newspaper articles. The analysis of causal constructions, the causal markers and their syntactic relation lead to the identification of different features for developing the language model using RBMs (Restricted Boltzmann Machine). The experiments we performed have given encouraging results. The Cause-Effect system developed is used in a mobile App for Event profiling called “Nigalazhvi” where the cause and effect of an event is identified and given to the user.

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