Graduation Semester and Year
2019
Language
English
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science and Engineering
First Advisor
Chengkai Li
Abstract
News headlines around the world are alarming. They aim to trigger emotional responses from the consumer. In an era where news and social media posts spread so quickly, it is often difficult to distinguish between what is real and what is false. Human fact-checking fails to cope with the growth of such unprecedented information, thus increasing the demand and various steps of automatic fact-checking to judge the veracity of claims. An automatic fact-checking system is a statistical model that can help to detect misinformation. The current state-of-the-art frame semantic parsers suffer from lack of a large annotated data-set and there are limited annotation tools available. So, we introduce how Frame Annotator, a web-based frame semantic annotation tool, uses natural language processing and the concept of frame semantics to help users to generate annotated data-sets.
Keywords
FrameAnnotator, Semantic role labeling, Fact-checking, IDIR, Frames
Disciplines
Computer Sciences | Physical Sciences and Mathematics
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Roy, Sarbajit, "FrameAnnotator - A Web-Based Frame Semantic Annotation Tool" (2019). Computer Science and Engineering Theses. 377.
https://mavmatrix.uta.edu/cse_theses/377
Comments
Degree granted by The University of Texas at Arlington