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Aligning English Sentences with Abstract Meaning Representation Graphs using Inductive Logic Programming


Abstract In this thesis, I propose a new technique of Aligning English sentence words

with its Semantic Representation using Inductive Logic Programming(ILP). My

work focusses on Abstract Meaning Representation(AMR). AMR is a semantic

formalism to English natural language. It encodes meaning of a sentence in a rooted

graph. This representation has gained attention for its simplicity and expressive power.

An AMR Aligner aligns words in a sentence to nodes(concepts) in its AMR

graph. As AMR annotation has no explicit alignment with words in English sentence,

automatic alignment becomes a requirement for training AMR parsers. The aligner in

this work comprises of two components. First, rules are learnt using ILP that invoke

AMR concepts from s... (more)
Created Date 2017
Contributor Agarwal, Shubham (Author) / Baral, Chitta (Advisor) / Li, Baoxin (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Subject Computer science
Type Masters Thesis
Extent 65 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Masters Thesis Computer Science 2017
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis