<?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%">Ekaterina Ovchinnikova</style></author><author><style face="normal" font="default" size="100%">Laure Vieu</style></author><author><style face="normal" font="default" size="100%">Alessandro Oltramari</style></author><author><style face="normal" font="default" size="100%">Stefano Borgo</style></author><author><style face="normal" font="default" size="100%">Theodore Alexandrov</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Nicoletta Calzolari (Conference Chair)</style></author><author><style face="normal" font="default" size="100%">Khalid Choukri</style></author><author><style face="normal" font="default" size="100%">Bente Maegaard</style></author><author><style face="normal" font="default" size="100%">Joseph Mariani</style></author><author><style face="normal" font="default" size="100%">Jan Odjik</style></author><author><style face="normal" font="default" size="100%">Stelios Piperidis</style></author><author><style face="normal" font="default" size="100%">Mike Rosner</style></author><author><style face="normal" font="default" size="100%">Daniel Tapias</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Data-Driven and Ontological Analysis of FrameNet for Natural Language Reasoning</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">may</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.lrec-conf.org/proceedings/lrec2010/pdf/84_Paper.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">European Language Resources Association (ELRA)</style></publisher><pub-location><style face="normal" font="default" size="100%">Valletta, Malta</style></pub-location><isbn><style face="normal" font="default" size="100%">2-9517408-6-7</style></isbn><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%">Ekaterina Ovchinnikova</style></author><author><style face="normal" font="default" size="100%">Niloofar Montazeri</style></author><author><style face="normal" font="default" size="100%">Theodore Alexandrov</style></author><author><style face="normal" font="default" size="100%">Jerry R. Hobbs</style></author><author><style face="normal" font="default" size="100%">Michael C. McCord</style></author><author><style face="normal" font="default" size="100%">Rutu Mulkar-Mehta</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Abductive Reasoning with a Large Knowledge Base for Discourse Processing</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of IWCS 2011</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">Submitted</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents a discourse processing framework based on weighted abduction. We elaborate on ideas described in Hobbs et al. (1993) and implement the abductive inference procedure in a system called Mini-TACITUS. Particular attention is paid to constructing a large and reliable knowledge base for supporting inferences. For this purpose we exploit such lexical-semantic resources as WordNet and FrameNet. We test the proposed procedure and the obtained knowledge base on the Recognizing Textual Entailment task using the data sets from the RTE-2 challenge for evaluation. In addition, we provide an evaluation of the semantic role labeling produced by the system taking the Frame-Annotated Corpus for Textual Entailment as a gold standard.</style></abstract></record></records></xml>