A Hybrid Approach to Inferring a Consistent Temporal Relation Set in Natural Language Text
Creator
Lee, Chong Min
Advisor
Katz, Graham E
Abstract
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.
Description
Ph.D.
Permanent Link
http://hdl.handle.net/10822/559494Date Published
2013Subject
Type
Publisher
Georgetown University
Extent
203 leaves
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Metadata
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