Dissertations, Theses, and Capstone Projects
Date of Degree
6-2016
Document Type
Thesis
Degree Name
M.A.
Program
Linguistics
Advisor
William Sakas
Subject Categories
Computational Linguistics | Discourse and Text Linguistics | Semantics and Pragmatics
Keywords
event extraction, semantic parsing
Abstract
While event extraction and automatic summarization have taken great strides in the realm of news stories, fictional narratives like fairy tales have not been so fortunate. A number of challenges arise from the literary elements present in fairy tales that are not found in more straightforward corpora of natural language, such as archaic expressions and sentence structures. To aid in summarization of fictional texts, I created an class - a template for a digital object, in this case a semantic and story event - that captures elements predicted to help classify events as important for inclusion. I wrote a processor to run over a new corpus of fairy tales and parse them into events, then to be manually annotated for importance and clustered to create a classifier that could be used on novel texts. These two latter steps could not be completed before publication of this paper, but my proposed approach is covered extensively, as is future work along the same lines. Along with this paper, supplementary materials encompassing the event class, processor code, corpus in full text, and corpus as un-annotated event data are included.
Recommended Citation
Lovering, Rebecca, "Event Parsing In Narrative: Trials And Tribulations Of Archaic English Fairy Tales" (2016). CUNY Academic Works.
https://academicworks.cuny.edu/gc_etds/1306
Event class, parser code, and readme file
StoryTime_Output.zip (7106 kB)
Included in
Computational Linguistics Commons, Discourse and Text Linguistics Commons, Semantics and Pragmatics Commons