tech,1-4-H01-1001,ak . Traditional <term> information retrieval techniques </term> use a <term> histogram </term> of <term>
tech,12-1-H01-1042,ak efficacy of applying <term> automated evaluation techniques </term> , originally devised for the <term>
tech,4-2-H01-1042,ak </term> . We believe that these <term> evaluation techniques </term> will provide information about both
tech,28-4-H01-1055,ak overcome by employing <term> machine learning techniques </term> . In this paper , we address the
tech,7-4-P01-1007,ak In this paper , we study a <term> parsing technique </term> whose purpose is to improve the practical
formal computation of the logical form . Techniques for automatically training modules of a
mechanisms and the other adopting statistical techniques . We present our <term> multi-level answer
tech,5-1-N03-1026,ak ambiguity packing and stochastic disambiguation techniques </term> for <term> Lexical-Functional Grammars
tech,4-1-N03-2015,ak . We describe a simple <term> unsupervised technique </term> for learning <term> morphology </term>
performance to more complex mixtures of techniques . We present a <term> syntax-based constraint
introduce a number of new performance enhancing techniques including <term> part of speech tagging </term>
tech,4-1-P03-2036,ak empirical comparison of <term> CFG filtering techniques </term> for <term> LTAG </term> and <term> HPSG
tech,3-4-H05-1012,ak improvement over <term> traditional word alignment techniques </term> is shown as well as improvement on
are focused on <term> parsing </term> , the techniques described generalize naturally to NLP structures
</term> . Basic methodology and practical techniques are reported in detail . The resultant <term>
tech,4-4-I05-5003,ak Our results show that <term> MT evaluation techniques </term> are able to produce useful features
lesser extent <term> entailment </term> . Our technique gives a substantial improvement in <term>
tech,5-1-P05-1046,ak many current <term> information extraction techniques </term> is severely limited by the need for
tech,1-3-P05-1074,ak available resource . Using <term> alignment techniques </term> from <term> phrase-based statistical
tech,1-2-P05-2008,ak negative . Traditional <term> machine learning techniques </term> have been applied to this problem
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