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Political events can be defined as a meeting or gathering of two or more people in order to elicit a political goal, agenda, or influence. In this research, a case study is used to showcase student learning from participating in a political events course and the execution of a nonpartisan mock caucus political event. This study extends our understanding of experiential learning in event management education and extends our understanding of political event planning, an underdeveloped and under researched aspect of event planning.

Anaphora resolution is complex problem in linguistics and has attracted the attention of many researchers. It is the problem of identifying referents in the discourse. Anaphora Resolution plays an important role in Natural language processing task. This paper completely emphasis on pronominal anaphora resolution for English Language in which pronouns refers to the intended noun in discourse. In this paper two computational models are proposed for anaphora resolution. Resolution of anaphora is based on various factors among which these models use Recency factor and Animistic Knowledge. Recency factor is implemented by using Lappin Leass approach in first model and using Centering approach in second model. Information about animacy is obtained by Gazetteer method. The identification of animistic elements is employed to improve the accuracy of the system. This paper demonstrates experiment conducted by both the models on different data sets from different domains. A comparative result of both the model is summarized and conclusion is drawn for the best suitable model.

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