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Using a Cognitive Architecture in Incremental Sentence Processing

XNL-Soar is a specialized implementation of the Soar cognitive architecture. The version of XNL-Soar described in this thesis builds upon and extends prior research (Lewis, 1993; Rytting,2000) using Soar for natural language processing. This thesis describes the updates made to operators creating syntactic structure and the improved coverage of syntactic phenomena. It describes the addition of semantic structure building capability. This thesis also details the implementation of semantic memory and describes two experiments utilizing semantic memory in structural disambiguation. This thesis shows that XNL-Soar, as currently instantiated, resolves ambiguities common in language using strategies and resources including: reanalysis via snip operators, use of data-driven techniques with annotated corpora, and complex part-of-speech and word sense processing based on WordNet.

Identiferoai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-4498
Date10 December 2012
CreatorsMcGhee, Jeremiah Lane
PublisherBYU ScholarsArchive
Source SetsBrigham Young University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations
Rightshttp://lib.byu.edu/about/copyright/

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