W00-0312 believe that using an appropriate grammar approximation algorithm to reduce the complexity
W11-2923 approach is more suitable for the grammar approximation task where training data can
W11-2923 corpus-driven approach towards grammar approximation for a linguistically deep Head-driven
W11-2923 is important to note that the grammar approximation task we take on in this paper
P07-1105 that is why our model is called Grammar Approximation by Representative Sublanguage
P07-1105 model for LWFG induction , called Grammar Approximation by Representative Sublanguage
P04-1047 , wide-coverage PCFG-based LFG grammar approximations automatically acquired from the
P04-1047 wide-coverage , probabilistic LFG grammar approximations and lexical resources for German
W05-1504 true weights . And though regular grammar approximations are useful for other purposes
P07-1105 level of performance . <title> Grammar Approximation by Representative Sublanguage
W08-2002 theoretical learning model is Grammar Approximation by Representative Sublanguage
J05-3003 wide-coverage , probabilistic LFG grammar approximations and lexical resources for German
W11-2923 set of " gold " trees , in the grammar approximation task we have access to the theoretically
C02-1075 Moore , 1999 ) 's approach to grammar approximation to ( Kiefer and Krieger , 2000
E12-1047 current work . 4 Context-free grammar approximation for coarse-to-fine parsing Coarse-to-fine
M93-1011 including Pereira 's research on grammar approximation -LSB- 4 -RSB- , som e of the
W00-0312 existing technology , whether grammar approximations or other techniques can produce
P07-1105 representative examples . 4.2 Grammar Approximation by Representative Sublanguage
J05-3003 wide-coverage probabilistic LFG grammar approximations automatically acquired from the
P07-1105 theoretical learning model , ) . called Grammar Approximation by Representative Sublanguage
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