Extracting Semantic Propositions from Dependency Trees
Name
Reio Laabus
Abstract
The main goal of this thesis is to implement a tool for extracting propositions from dependency parse trees. Propositions are part of sentences that describe the ideas what people want to express. Finding the propositions and counting them has been found to be good measurement to relate it with readability, memory or prediction of Alzheimer’s disease. Earlier works have extracted the propositions manually, my program called Proposition Count based on Patterns, short for PCP, does it automatically using patterns. Patterns are regular expressions that are created on the basis of AID manual and they are classified into 3 groups: predications, modifications and connectives. Patterns are used on depend-ency parse trees that present the syntactic structure of a sentence. It has been found that the dependency structure and propositions suit more naturally and is direct. The results depend a lot on correctness of the sentence, because parsers are not able to correctly parse faulty sentence and patterns can’t extract correct propositions from incorrect sentences. Results are also affected by what parser is being used, if using different parser than I used with the same patterns, then the possibility that extracting different count of propositions is high.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Kairit Sirts
Defence year
2017