In this dissertation, we first present our hybrid system to automatically extract temporal information from raw text by extracting events, temporal expressions and identifying temporal relations between entities. Our system had a competitive performance in the temporal evaluation shared task - TempEval 2010. Then we present a metric that we developed for the evaluation of temporal annotation. Our metric has been adopted by the premier temporal evaluation shared task, TempEval 2013, to evaluate participating systems. We also present a question-answering (QA) system that can answer temporal questions with temporal reasoning. Our developed QA system can be used to evaluate temporal information understanding capability. Finally, we describe our contributions in improving the existing temporal resources.
Thesis manuscript can be found at: http://bit.ly/nthesis