P09-1051 evaluation is within an unsupervised lexical expansion scenario applied to a text categorization
N09-2009 obtaining a special variant of lexical expansion . 1 Introduction Topical Text
P09-2018 one of its major applications is lexical expansion , which is generally asymmetric
P13-2051 words . Our evaluation shows that lexical expansion significantly improves performance
P09-1051 dure . Thus , some of our valid lexical expansions might retrieve non-annotated
P09-2018 annotated in the corpus . For our lexical expansion evaluation we considered the
D15-1103 entity-specific context , we make use of lexical expansions , which have been successfully
P09-2018 preliminary data analysis for lexical expansion . Finally , we note that in related
P09-2018 at least twice . As a typical lexical expansion task we used the ACE 2005 events
C96-1081 Section 3 explains the use of lexical expansion rules , whereas some concluding
P13-2051 step scheme . First , we learn lexical expansion sets for argument words , such
P09-1051 constructed baselines in a couple of lexical expansion and matching tasks . Our rule-base
P09-1051 recall , indicating the need for lexical expansion . The second baseline is our
H89-2008 development of a new module for lexical expansion via phonological rules , and
D11-1140 online , repeatedly performing both lexical expansion ( Step 1 ) and a parameter update
J12-4006 nonterminal ) rules in ( 2a -- c ) and lexical expansions in ( 2d -- f ) . Annotated lexical
D15-1103 entity-specific context ( using lexical expansions ) . We take all words in the
P13-2051 languages perfectly . <title> Using Lexical Expansion to Learn Inference Rules from
P09-2018 directional similarity measures for lexical expansion , and potentially for other tasks
P13-2051 application task show that our lexical expansion approach significantly improves
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