D09-1122 unary templates . Compared to verb entailment acquisition , the accuracy of both methods
N06-1007 among the five alternatives . Our entailment acquisition method generates association
N06-1007 illustrates such a test item . The entailment acquisition method was evaluated on entailment
D09-1122 based similarity measure to verb entailment acquisition . In addition , the trick implemented
D09-1122 section presents our method of verb entailment acquisition . First , the basics of Japanese
D09-1122 proposes a novel method for verb entailment acquisition . Using a Japanese Web corpus
D09-1122 our method can also perform the entailment acquisition of unary templates . We presented
D09-1122 Pairs This section presents the entailment acquisition accuracy for template pairs to
D09-1122 when applied to template-level entailment acquisition in § 4.4 . Finally , by
N06-1007 accuracy scores achieved by our entailment acquisition algorithm , the two human judges
N06-1007 consequence Q . The goal of verb entailment acquisition is then to find two linguistic
D09-1122 2004 ) addressed broad coverage entailment acquisition . But their method requires an
D09-1122 improves the accuracy of verb entailment acquisition . In an evaluation of the top
D09-1122 this trick actually improved the entailment acquisition accuracy . We used maximum likelihood
D09-1122 Conclusion This paper addressed verb entailment acquisition from the Web , and proposed a
D09-1122 of the trick . We examine the entailment acquisition accuracy for frequent verbs in
D09-1025 rule-based one on the task of lexical entailment acquisition . The large set of features adopted
D09-1122 Japan ) . <title> Large-Scale Verb Entailment Acquisition from the Web </title> Kentaro
D09-1122 . Though most of the previous entailment acquisition studies focused on binary templates
N06-1007 verbs , the main challenge of entailment acquisition is to capture asymmetric , or
hide detail