Temporal Processing of News: Annotation of Temporal Expressions, Verbal Events and Temporal Relations
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AbstractThe ability to capture the temporal dimension of a natural language text is essential to many natural language processing applications, such as Question Answering, Automatic Summarisation, and Information Retrieval. Temporal processing is a ¯eld of Computational Linguistics which aims to access this dimension and derive a precise temporal representation of a natural language text by extracting time expressions, events and temporal relations, and then representing them according to a chosen knowledge framework. This thesis focuses on the investigation and understanding of the di®erent ways time is expressed in natural language, on the implementation of a temporal processing system in accordance with the results of this investigation, on the evaluation of the system, and on the extensive analysis of the errors and challenges that appear during system development. The ultimate goal of this research is to develop the ability to automatically annotate temporal expressions, verbal events and temporal relations in a natural language text. Temporal expression annotation involves two stages: temporal expression identi¯cation concerned with determining the textual extent of a temporal expression, and temporal expression normalisation which ¯nds the value that the temporal expression designates and represents it using an annotation standard. The research presented in this thesis approaches these tasks with a knowledge-based methodology that tackles temporal expressions according to their semantic classi¯cation. Several knowledge sources and normalisation models are experimented with to allow an analysis of their impact on system performance. The annotation of events expressed using either ¯nite or non-¯nite verbs is addressed with a method that overcomes the drawback of existing methods v which associate an event with the class that is most frequently assigned to it in a corpus and are limited in coverage by the small number of events present in the corpus. This limitation is overcome in this research by annotating each WordNet verb with an event class that best characterises that verb. This thesis also describes an original methodology for the identi¯cation of temporal relations that hold among events and temporal expressions. The method relies on sentence-level syntactic trees and a propagation of temporal relations between syntactic constituents, by analysing syntactic and lexical properties of the constituents and of the relations between them. The detailed evaluation and error analysis of the methods proposed for solving di®erent temporal processing tasks form an important part of this research. Various corpora widely used by researchers studying di®erent temporal phenomena are employed in the evaluation, thus enabling comparison with state of the art in the ¯eld. The detailed error analysis targeting each temporal processing task helps identify not only problems of the implemented methods, but also reliability problems of the annotated resources, and encourages potential reexaminations of some temporal processing tasks.
PublisherUniversity of Wolverhampton
TypeThesis or dissertation
DescriptionA thesis submitted by Georgiana Marşic.
Showing items related by title, author, creator and subject.
Historical ‘Signposts’ and Other Temporal Indicators in the Czech LexiconDickins, Tom (JSTOR, 2012)This article posits that the Czechs employ a great many historical markers, previously applied to other events of national importance, which help to shape collective memory and right the ‘wrongs’ of the past. It is argued that these temporal indicators share a number of clearly defined characteristics, and that their use is too systematic and calculated to be merely a function of the constraints of the lexicon. The first part of the study considers in detail questions of semantics (especially the distinction between denotation and connotation), the lexicographical sources available to the researcher, and the lexical ‘signpost’ in context, while the second part focuses on practical examples of lexical re-appropriation since 1918, with particular reference to dictionaries and the Czech National Corpus.