Date of Degree

6-2014

Document Type

Dissertation

Degree Name

Ph.D.

Program

Linguistics

Advisor

Heng Ji

Subject Categories

Computer Sciences | Linguistics

Keywords

Event Ordering, Temporal Knowledge Base Population, Temporal Relation Extraction, Temporal Slot Filling

Abstract

Temporal Information Extraction (TIE) from text plays an important role in many Natural Language Processing and Database applications. Many features of the world are time-dependent, and rich temporal knowledge is required for a more complete and precise understanding of the world. In this thesis we address aspects of two core tasks in TIE. First, we provide a new corpus of labeled temporal relations between events and temporal expressions, dense enough to facilitate a change in research directions from relation classification to identification, and present a system designed to address corresponding new challenges. Second, we implement a novel approach for the discovery and aggregation of temporal information about entity-centric fluent relations.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.