Difference between revisions of "More details on Phrasal discriminative features"

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=== Discriminative Phrase Table ===
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Various discriminative features could be specified under the [additional-featurizers] section in Phrasal *.ini files.
Specify in the *.ini file under [
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The following options are available:
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  "bleu" --  the percentage of common n-grams found in machine and reference translations (Papineni et al., 2002).
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  "ter"  --  translation edit rate, i.e. shortest edit sequence to turn a machine translation into a reference (Snover et al., 2006).
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  "terp" --  a variant of TER with synonym and paraphrase matching turned on (super slow) (Snover et al., 2009).
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  "nist" --  a variant of BLEU which weights n-gram matches by how informative they are (Doddington, 2002).
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  "wer"  --  word error rate (Nießen et al., 2000).
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  "per"
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  "bleu-ter:w" -- linearly combine BLEU and TER with the weight w placed on TER, i.e. BLEU + w*TER. "bleu-ter" implies w=1.0.
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For a comparison of these various metrics, see:
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=== Discriminative Phrase Table ===
@inproceedings{Cer:2010:BLM,
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edu.stanford.nlp.mt.decoder.feat.sparse.DiscriminativePhraseTable(arg1,arg2,arg3)
  author = {Cer, Daniel and Manning, Christopher D. and Jurafsky, Daniel},
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   "arg1" --  true/false, whether to use lexicalized features or not (default=true)
   title = {The best lexical metric for phrase-based statistical MT system optimization},
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   "arg2" --  true/false, whether to use class-based features or not (default=false)
   booktitle = {Proceedings of NAACL},
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   "arg3" --  int, whether to threshold feature count (default=-1, no thresholding)
   year = {2010},
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}
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Revision as of 14:45, 16 January 2014

Various discriminative features could be specified under the [additional-featurizers] section in Phrasal *.ini files.

Discriminative Phrase Table

edu.stanford.nlp.mt.decoder.feat.sparse.DiscriminativePhraseTable(arg1,arg2,arg3)

 "arg1" --  true/false, whether to use lexicalized features or not (default=true)
 "arg2" --  true/false, whether to use class-based features or not (default=false)
 "arg3" --  int, whether to threshold feature count (default=-1, no thresholding)