Difference between revisions of "User:Francis Tyers/TLH"

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==Tarea 1==
==Tarea 1==
<pre>
<pre>
for x in `seq 0 9`; do
$ evaluate.pl LexEsp-0.cooked LexEsp-0.t3
cooked2lex.pl < LexEsp-train-$x.cooked > train-$x.lex
cooked2ngram.pl < LexEsp-train-$x.cooked > train-$x.ngrams
cooked2raw.pl < LexEsp-$x.cooked > LexEsp-$x.raw
t3 train-$x.ngrams train-$x.lex < LexEsp-$x.raw > LexEsp-$x.t3
evaluate.pl LexEsp-$x.cooked LexEsp-$x.t3 >> output
done

$ cat output
418 sentences
418 sentences
LexEsp-0.t3 9470 397 95.976%
LexEsp-0.t3 9470 397 95.976%
418 sentences
LexEsp-1.t3 9290 410 95.773%
418 sentences
LexEsp-2.t3 9199 430 95.534%
418 sentences
LexEsp-3.t3 9264 440 95.466%
418 sentences
LexEsp-4.t3 9164 448 95.339%
418 sentences
LexEsp-5.t3 8908 397 95.733%
418 sentences
LexEsp-6.t3 8968 418 95.547%
418 sentences
LexEsp-7.t3 9334 414 95.753%
418 sentences
LexEsp-8.t3 9693 478 95.300%
417 sentences
LexEsp-9.t3 9434 405 95.884%

</pre>
</pre>


Line 80: Line 107:


==Tarea 4==
==Tarea 4==
<pre>

$ prepare-corpus.sh LexEsp_Etq_Larga.cooked
$ prepare-corpus.sh LexEsp_Etq_Larga.cooked
4179 sentences
4179 sentences
Line 93: Line 120:
Entropy H(p)=5.488119
Entropy H(p)=5.488119


$ for x in `seq 0 9`; do
$ cooked2lex.pl < LexEsp_Etq_Larga-train-0.cooked > train.larga.lex
3761 sentences
254 tags 15431 types 87094 tokens
1 14742 95.535% 62581 71.855%
2 637 4.128% 20044 23.014%
3 47 0.305% 3620 4.156%
4 2 0.013% 96 0.110%
5 3 0.019% 753 0.865%
Mean ambiguity A=1.351161


cooked2lex.pl < LexEsp_Etq_Larga-train-$x.cooked > train-$x.lex
Entropy H(p)=5.485330
cooked2ngram.pl < LexEsp_Etq_Larga-train-$x.cooked > train-$x.ngrams
cooked2raw.pl < LexEsp_Etq_Larga-$x.cooked > LexEsp_Etq_Larga-$x.raw
t3 train-$x.ngrams train-$x.lex < LexEsp_Etq_Larga-$x.raw > LexEsp_Etq_Larga-$x.t3
evaluate.pl LexEsp_Etq_Larga-$x.cooked LexEsp_Etq_Larga-$x.t3 >> output


done
$ cooked2ngram.pl < LexEsp_Etq_Larga-train-0.cooked > train.larga.ngrams
$ cooked2raw.pl LexEsp_Etq_Larga-0.cooked > LexEsp_Etq_Larga-0.raw
$ cooked2raw.pl < LexEsp_Etq_Larga-0.cooked > LexEsp_Etq_Larga-0.raw
$ t3 train.larga.ngrams train.larga.lex < LexEsp_Etq_Larga-0.raw > LexEsp_Etq_Larga-0.t3
[ 4 ms::1]
[ 4 ms::1] Trigram POS Tagger (c) Ingo Schr�der, schroeder@informatik.uni-hamburg.de
[ 4 ms::1]
[ 2064 ms::1] model generated from 3761 sentences (thereof 43 one-word)
[ 2064 ms::1] found 11283 uni-, 15044 bi-, and 18762 trigram counts for the boundary tag
[ 12724 ms::1] computed smoothed transition probabilities
[ 13512 ms::1] built suffix tries with 29924 lowercase and 6743 uppercase nodes
[ 13532 ms::1] leaves/single/total LC: 7672 18878 29925
[ 13536 ms::1] leaves/single/total UC: 1320 4874 6744
[ 16329 ms::1] suffix probabilities smoothing done [theta 1.281e-02]
[ 12249377 ms::1] done

$ evaluate.pl LexEsp_Etq_Larga-0.cooked LexEsp_Etq_Larga-0.t3


$ cat output
418 sentences
418 sentences
LexEsp_Etq_Larga-0.t3 9412 455 95.389%
LexEsp_Etq_Larga-0.t3 9412 455 95.389%
418 sentences
LexEsp_Etq_Larga-1.t3 9206 494 94.907%
418 sentences
LexEsp_Etq_Larga-2.t3 9123 506 94.745%
418 sentences
LexEsp_Etq_Larga-3.t3 9208 496 94.889%
418 sentences
LexEsp_Etq_Larga-4.t3 9105 507 94.725%
418 sentences
LexEsp_Etq_Larga-5.t3 8846 459 95.067%
418 sentences
LexEsp_Etq_Larga-6.t3 8893 493 94.747%
418 sentences
LexEsp_Etq_Larga-7.t3 9258 490 94.973%
418 sentences
LexEsp_Etq_Larga-8.t3 9645 526 94.828%
417 sentences
LexEsp_Etq_Larga-9.t3 9355 484 95.081%

</pre>

Latest revision as of 15:09, 6 April 2008

Tarea 1[edit]

for x in `seq 0 9`; do 
        cooked2lex.pl < LexEsp-train-$x.cooked > train-$x.lex
        cooked2ngram.pl < LexEsp-train-$x.cooked > train-$x.ngrams
        cooked2raw.pl < LexEsp-$x.cooked > LexEsp-$x.raw
        t3 train-$x.ngrams train-$x.lex < LexEsp-$x.raw > LexEsp-$x.t3
        evaluate.pl LexEsp-$x.cooked LexEsp-$x.t3 >> output
done

$ cat output 
418 sentences
         LexEsp-0.t3     9470      397  95.976%
418 sentences
         LexEsp-1.t3     9290      410  95.773%
418 sentences
         LexEsp-2.t3     9199      430  95.534%
418 sentences
         LexEsp-3.t3     9264      440  95.466%
418 sentences
         LexEsp-4.t3     9164      448  95.339%
418 sentences
         LexEsp-5.t3     8908      397  95.733%
418 sentences
         LexEsp-6.t3     8968      418  95.547%
418 sentences
         LexEsp-7.t3     9334      414  95.753%
418 sentences
         LexEsp-8.t3     9693      478  95.300%
417 sentences
         LexEsp-9.t3     9434      405  95.884%

Tarea 2[edit]

$ for i in `seq 1 9`; do 
    cat LexEsp-[1-$i].cooked > LexEsp-ejecucion$i.cooked; 
    cooked2lex.pl < LexEsp-ejecucion$i.cooked > train.$i.lex; 
    cooked2ngram.pl < LexEsp-ejecucion$i.cooked > train.$i.ngrams; 
    t3 train.$i.ngrams train.$i.lex < LexEsp-0.raw > LexEsp-0.$i.t3; 
    evaluate.pl LexEsp-0.cooked LexEsp-0.$i.t3 >> output ; 
done

$ wc -l LexEsp-ejecucion*.cooked
    418 LexEsp-ejecucion1.cooked
    836 LexEsp-ejecucion2.cooked
   1254 LexEsp-ejecucion3.cooked
   1672 LexEsp-ejecucion4.cooked
   2090 LexEsp-ejecucion5.cooked
   2508 LexEsp-ejecucion6.cooked
   2926 LexEsp-ejecucion7.cooked
   3344 LexEsp-ejecucion8.cooked
   3761 LexEsp-ejecucion9.cooked

$ cat output
418 sentences
       LexEsp-0.1.t3     8948      919  90.686%
418 sentences
       LexEsp-0.2.t3     9155      712  92.784%
418 sentences
       LexEsp-0.3.t3     9275      592  94.000%
418 sentences
       LexEsp-0.4.t3     9313      554  94.385%
418 sentences
       LexEsp-0.5.t3     9366      501  94.922%
418 sentences
       LexEsp-0.6.t3     9391      476  95.176%
418 sentences
       LexEsp-0.7.t3     9419      448  95.460%
418 sentences
       LexEsp-0.8.t3     9444      423  95.713%
418 sentences
       LexEsp-0.9.t3     9470      397  95.976%

Tarea 3[edit]

$ for i in `seq 1 10`; do 
    t3 -l $i train.ngrams train.lex < LexEsp-0.raw > LexEsp-0.l$i.t3; 
    evaluate.pl LexEsp-0.cooked LexEsp-0.l$i.t3 >> output.l; 
done

$ cat output.l
418 sentences
      LexEsp-0.l1.t3     9411      456  95.379%
418 sentences
      LexEsp-0.l2.t3     9466      401  95.936%
418 sentences
      LexEsp-0.l3.t3     9492      375  96.199%
418 sentences
      LexEsp-0.l4.t3     9490      377  96.179%
418 sentences
      LexEsp-0.l5.t3     9473      394  96.007%
418 sentences
      LexEsp-0.l6.t3     9477      390  96.047%
418 sentences
      LexEsp-0.l7.t3     9473      394  96.007%
418 sentences
      LexEsp-0.l8.t3     9470      397  95.976%
418 sentences
      LexEsp-0.l9.t3     9470      397  95.976%
418 sentences
     LexEsp-0.l10.t3     9470      397  95.976%

Tarea 4[edit]

$ prepare-corpus.sh LexEsp_Etq_Larga.cooked
4179 sentences
256 tags 16481 types 96961 tokens
  1     15735  95.474%     69045  71.209% 
  2       689   4.181%     22621  23.330% 
  3        51   0.309%      4315   4.450% 
  4         3   0.018%       151   0.156% 
  5         3   0.018%       829   0.855% 
Mean ambiguity A=1.361176

Entropy H(p)=5.488119

$ for x in `seq 0 9`; do 

        cooked2lex.pl < LexEsp_Etq_Larga-train-$x.cooked > train-$x.lex
        cooked2ngram.pl < LexEsp_Etq_Larga-train-$x.cooked > train-$x.ngrams
        cooked2raw.pl < LexEsp_Etq_Larga-$x.cooked > LexEsp_Etq_Larga-$x.raw
        t3 train-$x.ngrams train-$x.lex < LexEsp_Etq_Larga-$x.raw > LexEsp_Etq_Larga-$x.t3
        evaluate.pl LexEsp_Etq_Larga-$x.cooked LexEsp_Etq_Larga-$x.t3 >> output

done

$ cat output
418 sentences
LexEsp_Etq_Larga-0.t3     9412      455  95.389%
418 sentences
LexEsp_Etq_Larga-1.t3     9206      494  94.907%
418 sentences
LexEsp_Etq_Larga-2.t3     9123      506  94.745%
418 sentences
LexEsp_Etq_Larga-3.t3     9208      496  94.889%
418 sentences
LexEsp_Etq_Larga-4.t3     9105      507  94.725%
418 sentences
LexEsp_Etq_Larga-5.t3     8846      459  95.067%
418 sentences
LexEsp_Etq_Larga-6.t3     8893      493  94.747%
418 sentences
LexEsp_Etq_Larga-7.t3     9258      490  94.973%
418 sentences
LexEsp_Etq_Larga-8.t3     9645      526  94.828%
417 sentences
LexEsp_Etq_Larga-9.t3     9355      484  95.081%