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        <title>Finding the Causality of an Event in News Articles</title>
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        <namePart type="given">Sobha</namePart>
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            <title>Proceedings of the 7th Workshop on Indian Language Data: Resources and Evaluation</title>
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            <namePart type="given">Girish</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T Finding the Causality of an Event in News Articles
%A Lalitha Devi, Sobha
%A RK Rao, Pattabhi
%Y Jha, Girish Nath
%Y L., Sobha
%Y Bali, Kalika
%Y Ojha, Atul Kr.
%S Proceedings of the 7th Workshop on Indian Language Data: Resources and Evaluation
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F lalitha-devi-rk-rao-2024-finding
%X 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.
%U https://aclanthology.org/2024.wildre-1.7
%P 47-53

Markdown (Informal)

[Finding the Causality of an Event in News Articles](https://aclanthology.org/2024.wildre-1.7) (Lalitha Devi & RK Rao, WILDRE-WS 2024)

• Finding the Causality of an Event in News Articles (Lalitha Devi & RK Rao, WILDRE-WS 2024)

ACL

• Sobha Lalitha Devi and Pattabhi RK Rao. 2024. Finding the Causality of an Event in News Articles. In Proceedings of the 7th Workshop on Indian Language Data: Resources and Evaluation, pages 47–53, Torino, Italia. ELRA and ICCL.