<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bahadorreza Ofoghi</style></author><author><style face="normal" font="default" size="100%">Yearwood, John</style></author><author><style face="normal" font="default" size="100%">Liping Ma</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Wayne Wobcke</style></author><author><style face="normal" font="default" size="100%">Mengjie Zhang</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">FrameNet-Based Fact-Seeking Answer Processing: A Study of Semantic Alignment Techniques and Lexical Coverage</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Artificial Intelligence: 21st Australasian Joint Conference on Artificial Intelligence Proceedings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://books.google.com/books?id=fSA1HKsw9tsC&amp;pg=PA192</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Auckland, New Zealand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bahadorreza Ofoghi</style></author><author><style face="normal" font="default" size="100%">Yearwood, John</style></author><author><style face="normal" font="default" size="100%">Ghosh, Ranadhir</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Within-Frame Ontological Extension on FrameNet: Application in Predicate Chain Analysis and Question Answering</style></title><secondary-title><style face="normal" font="default" size="100%">Australian Conference on Artificial Intelligence</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><pages><style face="normal" font="default" size="100%">404-414</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In satisfying an information need by a Question Answering (QA) system, there are text understanding approaches which can enhance the performance of final answer extraction. Exploiting the FrameNet lexical resource in this process inspires analysis of the levels of semantic representation in the automated practice where the task of semantic class and role labeling takes place. In this paper, we analyze the impact of different levels of semantic parsing on answer extraction with respect to the individual sub-tasks of frame evocation and frame element assignment.</style></abstract></record></records></xml>