D08-1002 have described a case study of contradiction detection ( CD ) based on functional relations
D10-1123 consider two sentences from a contradiction detection task : ( 1 ) " George Washington
P08-1118 broad coverage . 6 Results Our contradiction detection system was developed on all datasets
N10-4008 . Show how it can be used for contradiction detection . 4 . Knowledge Acquisition and
P08-1118 discussion One significant issue in contradiction detection is lack of feature generalization
P08-1118 to gain sufficient traction on contradiction detection for real world applications .
P14-1029 . For example , paraphrase and contradiction detection systems rely on detecting negated
W03-0906 concluding that entailment and contradiction detection is a suitable evaluation metric
P08-1118 linguistic intuition . 5 Features for contradiction detection In this section , we define each
P08-1118 to solve the entire problem of contradiction detection . Some types of these contradictions
D08-1002 Stephen Soderland Oren Abstract Contradiction Detection ( CD ) in text is a difficult
D12-1081 for various NLP tasks such as contradiction detection , quantifier scope disam - biguation
D13-1065 Harabagiu et al. ( 2006 ) proposed a contradiction detection method that focuses on negation
D10-1123 ( Ritter et al. , 2008 ) is a contradiction detection system that also learns relation
D10-1007 Although little work has been done on contradiction detection , there are a few notable approaches
J12-2001 Ritter et al. ( 2008 ) present a contradiction detection system that uses the TEXTRUNNER
D10-1123 such as synonym resolution and contradiction detection . Previous work on this problem
D08-1002 ; its precision and recall in contradiction detection ( Section 5.3 ) ; and the contribution
P08-1118 are both true . However , for contradiction detection to be useful , a looser definition
D10-1123 functionality for the tasks of contradiction detection ( Ritter et al. , 2008 ) , quantifier
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