| This dissertation investigates the temporal relation identification task. The goal is to construct consistent temporal relations between temporal entities (e.g., events and time expressions) in a narrative. Constructing consistent temporal relations is challenging due to the exponential increase in the number of candidates for temporal relations proportional to the number of pairs of temporal entities. When we use transitive constraints to construct consistent temporal relations, performance improvement can be expected because the application of transitive constraints reduces the number of possible relation candidates in a narrative.;The primary objective of this study is to develop a temporal relation identification (TRI) system that is composed of three modules: 1) a module that classifies the temporal relation of a pair of temporal entities, 2) a module that extracts conflicting classified relations using transitive constraints, and 3) a module that restores consistent temporal relations from the conflicting relations using transitive constraints. In developing a TRI system, this dissertation examines whether the application of transitive constraints to such a system can lead to performance improvement.;The first step in developing the system was to implement a rudimentary temporal relation classification module. The module labels a pair of temporal entities with a temporal relation among eleven possible temporal relations. Next, a method for extracting conflicting relations among classified relations is proposed. The extraction method is based on heuristics because of NP-hard complexity in extracting all conflicting relations. Finally, two heuristic methods are proposed that restore consistent temporal structure from conflicting relations using transitive constraints. The performance of the developed system is tested using TimeBank and AQUAINT temporal corpora.;The results of this work indicate that a performance improvement through the application of transitive constraints to TRI task is not guaranteed. Furthermore, this study empirically shows the limitations on performance improvement through the application of transitive constraints to the TRI task and identifies the bottlenecks in the TRI task.;INDEX WORDS: computational linguistics, natural language processing, temporal information processing, temporal relation extraction, temporal relation classification, temporal relation identification. |
