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Temporal Information Extraction (TIE) plays an important role in many natural language processing and database applications. Temporal slot filling (TSF) is a new and ambitious TIE task prepared for the knowledge base population (KBP2011) track of NIST Text Analysis Conference. TSF requires systems to discover temporally bound facts about entities and their attributes in order to populate a structured knowledge base. In this paper, we will provide an overview of the unique challenges of this new task and our novel approaches to address these challenges. We present challenges from three perspectives: (1) Temporal information representation: We will review the relevant linguistic semantic theories of temporal information and their limitations, motivating the need to develop a new (4-tuple) representation framework for the task. (2) Annotation acquisition: The lack of substantial labeled training data for …