Recognizing TimeML events and identifying their attributes, are important tasks in natural language processing (NLP). Several NLP applications like question answering, information retrieval, summarization, and temporal information extraction need to have some knowledge about events of the input documents. Existing methods developed for this task are restricted to limited number of languages, and for many other languages including Persian, there has not been any effort yet. In this paper, we

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... oduce two different approaches for automatic event recognition and classification in Persian. For this purpose, a corpus of events has been built based on a specific version of ISO-TimeML for Persian. We present the specification of this corpus together with the results of applying mentioned approaches to the corpus. Considering these methods are the first effort towards Persian event extraction, the results are comparable to that of successful methods in English.