diff options
| author | Patrick Simianer <p@simianer.de> | 2015-03-24 19:15:48 +0100 |
|---|---|---|
| committer | Patrick Simianer <p@simianer.de> | 2015-03-24 19:15:48 +0100 |
| commit | 70572bc0aa0338b298e9a8e2829a0a0d134785e4 (patch) | |
| tree | ddcea305027ff3ef1e1aea2e502898de00c718b3 /training/dtrain/examples/parallelized | |
| parent | bca9a8d79e565222898afbe98abf5ce5a1fe801b (diff) | |
dtrain: fix example
Diffstat (limited to 'training/dtrain/examples/parallelized')
45 files changed, 0 insertions, 31164 deletions
diff --git a/training/dtrain/examples/parallelized/README b/training/dtrain/examples/parallelized/README deleted file mode 100644 index c4addd81..00000000 --- a/training/dtrain/examples/parallelized/README +++ /dev/null @@ -1,5 +0,0 @@ -run for example - ../../parallelize.rb -c dtrain.ini -s 4 -e 3 -d ../../dtrain -p 2 -i in - -final weights will be in the file work/weights.2 - diff --git a/training/dtrain/examples/parallelized/cdec.ini b/training/dtrain/examples/parallelized/cdec.ini deleted file mode 100644 index 9a04253f..00000000 --- a/training/dtrain/examples/parallelized/cdec.ini +++ /dev/null @@ -1,26 +0,0 @@ -formalism=scfg -add_pass_through_rules=true -scfg_max_span_limit=15 -intersection_strategy=cube_pruning -cubepruning_pop_limit=200 -feature_function=WordPenalty -feature_function=KLanguageModel ../standard/nc-wmt11.en.srilm.gz -# all currently working feature functions for translation: -# (with those features active that were used in the ACL paper) -#feature_function=ArityPenalty -#feature_function=CMR2008ReorderingFeatures -#feature_function=Dwarf -#feature_function=InputIndicator -#feature_function=LexNullJump -#feature_function=NewJump -#feature_function=NgramFeatures -#feature_function=NonLatinCount -#feature_function=OutputIndicator -feature_function=RuleIdentityFeatures -feature_function=RuleSourceBigramFeatures -feature_function=RuleTargetBigramFeatures -feature_function=RuleShape -#feature_function=LexicalFeatures 1 1 1 -#feature_function=SourceSpanSizeFeatures -#feature_function=SourceWordPenalty -#feature_function=SpanFeatures diff --git a/training/dtrain/examples/parallelized/dtrain.ini b/training/dtrain/examples/parallelized/dtrain.ini deleted file mode 100644 index 829605fb..00000000 --- a/training/dtrain/examples/parallelized/dtrain.ini +++ /dev/null @@ -1,7 +0,0 @@ -k=100 -N=4 -learning_rate=0.0001 -margin=1.0 -iterations=1 -decoder_conf=cdec.ini -print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.0.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.0.gz Binary files differdeleted file mode 100644 index 1e28a24b..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.0.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.1.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.1.gz Binary files differdeleted file mode 100644 index 372f5675..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.1.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.2.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.2.gz Binary files differdeleted file mode 100644 index 145d0dc0..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.2.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.3.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.3.gz Binary files differdeleted file mode 100644 index 105593ff..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.3.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.4.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.4.gz Binary files differdeleted file mode 100644 index 30781f48..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.4.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.5.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.5.gz Binary files differdeleted file mode 100644 index 834ee759..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.5.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.6.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.6.gz Binary files differdeleted file mode 100644 index 2e76f348..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.6.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.7.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.7.gz Binary files differdeleted file mode 100644 index 3741a887..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.7.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.8.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.8.gz Binary files differdeleted file mode 100644 index ebf6bd0c..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.8.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.9.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.9.gz Binary files differdeleted file mode 100644 index c1791059..00000000 --- a/training/dtrain/examples/parallelized/grammar/grammar.out.9.gz +++ /dev/null diff --git a/training/dtrain/examples/parallelized/in b/training/dtrain/examples/parallelized/in deleted file mode 100644 index 82555908..00000000 --- a/training/dtrain/examples/parallelized/in +++ /dev/null @@ -1,10 +0,0 @@ -<seg grammar="grammar/grammar.out.0.gz" id="0">europas nach rassen geteiltes haus</seg> ||| europe 's divided racial house -<seg grammar="grammar/grammar.out.1.gz" id="1">ein gemeinsames merkmal aller extremen rechten in europa ist ihr rassismus und die tatsache , daß sie das einwanderungsproblem als politischen hebel benutzen .</seg> ||| a common feature of europe 's extreme right is its racism and use of the immigration issue as a political wedge . -<seg grammar="grammar/grammar.out.2.gz" id="2">der lega nord in italien , der vlaams block in den niederlanden , die anhänger von le pens nationaler front in frankreich , sind beispiele für parteien oder bewegungen , die sich um das gemeinsame thema : ablehnung der zuwanderung gebildet haben und um forderung nach einer vereinfachten politik , um sie zu regeln .</seg> ||| the lega nord in italy , the vlaams blok in the netherlands , the supporters of le pen 's national front in france , are all examples of parties or movements formed on the common theme of aversion to immigrants and promotion of simplistic policies to control them . -<seg grammar="grammar/grammar.out.3.gz" id="3">während individuen wie jörg haidar und jean @-@ marie le pen kommen und ( leider nicht zu bald ) wieder gehen mögen , wird die rassenfrage aus der europäischer politik nicht so bald verschwinden .</seg> ||| while individuals like jorg haidar and jean @-@ marie le pen may come and ( never to soon ) go , the race question will not disappear from european politics anytime soon . -<seg grammar="grammar/grammar.out.4.gz" id="4">eine alternde einheimische bevölkerung und immer offenere grenzen vermehren die rassistische zersplitterung in den europäischen ländern .</seg> ||| an aging population at home and ever more open borders imply increasing racial fragmentation in european countries . -<seg grammar="grammar/grammar.out.5.gz" id="5">die großen parteien der rechten und der linken mitte haben sich dem problem gestellt , in dem sie den kopf in den sand gesteckt und allen aussichten zuwider gehofft haben , es möge bald verschwinden .</seg> ||| mainstream parties of the center left and center right have confronted this prospect by hiding their heads in the ground , hoping against hope that the problem will disappear . -<seg grammar="grammar/grammar.out.6.gz" id="6">das aber wird es nicht , wie die geschichte des rassismus in amerika deutlich zeigt .</seg> ||| it will not , as america 's racial history clearly shows . -<seg grammar="grammar/grammar.out.7.gz" id="7">die beziehungen zwischen den rassen standen in den usa über jahrzehnte - und tun das noch heute - im zentrum der politischen debatte . das ging so weit , daß rassentrennung genauso wichtig wie das einkommen wurde , - wenn nicht sogar noch wichtiger - um politische zuneigungen und einstellungen zu bestimmen .</seg> ||| race relations in the us have been for decades - and remain - at the center of political debate , to the point that racial cleavages are as important as income , if not more , as determinants of political preferences and attitudes . -<seg grammar="grammar/grammar.out.8.gz" id="8">der erste schritt , um mit der rassenfrage umzugehen ist , ursache und folgen rassistischer feindseligkeiten zu verstehen , auch dann , wenn das bedeutet , unangenehme tatsachen aufzudecken .</seg> ||| the first step to address racial politics is to understand the origin and consequences of racial animosity , even if it means uncovering unpleasant truths . -<seg grammar="grammar/grammar.out.9.gz" id="9">genau das haben in den usa eine große anzahl an forschungsvorhaben in wirtschaft , soziologie , psychologie und politikwissenschaft geleistet . diese forschungen zeigten , daß menschen unterschiedlicher rasse einander deutlich weniger vertrauen .</seg> ||| this is precisely what a large amount of research in economics , sociology , psychology and political science has done for the us . diff --git a/training/dtrain/examples/parallelized/work/out.0.0 b/training/dtrain/examples/parallelized/work/out.0.0 deleted file mode 100644 index da7c20a4..00000000 --- a/training/dtrain/examples/parallelized/work/out.0.0 +++ /dev/null @@ -1,44 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.0.0' - output 'work/weights.0.0' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = +0.1984 - WordPenalty = +0.06119 - LanguageModel = +0.6184 - LanguageModel_OOV = -0.2584 - PhraseModel_0 = -0.3803 - PhraseModel_1 = +0.6495 - PhraseModel_2 = +0.9499 - PhraseModel_3 = -0.4945 - PhraseModel_4 = -0.4588 - PhraseModel_5 = +0 - PhraseModel_6 = -0.2935 - PassThrough = -0.2742 - --- - 1best avg score: 22.94 (+22.94) - 1best avg model score: +33.08 - avg # updates: 2169 - non-0 feature count: 441 - avg f count: 143.9 - avg list sz: 100 -(time 0.1667 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 22.94]. -This took 0.1667 min. diff --git a/training/dtrain/examples/parallelized/work/out.0.1 b/training/dtrain/examples/parallelized/work/out.0.1 deleted file mode 100644 index c18747fb..00000000 --- a/training/dtrain/examples/parallelized/work/out.0.1 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.0.0' - output 'work/weights.0.1' - weights in 'work/weights.0' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = +0.08417 - WordPenalty = +0.1674 - LanguageModel = +0.5448 - LanguageModel_OOV = -0.6311 - PhraseModel_0 = -0.2931 - PhraseModel_1 = +1.173 - PhraseModel_2 = +1.369 - PhraseModel_3 = +0.1819 - PhraseModel_4 = -0.8439 - PhraseModel_5 = +0.02055 - PhraseModel_6 = -0.3794 - PassThrough = -0.6827 - --- - 1best avg score: 16.83 (+16.83) - 1best avg model score: +66.56 - avg # updates: 2090 - non-0 feature count: 2218 - avg f count: 142.5 - avg list sz: 100 -(time 0.1833 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 16.83]. -This took 0.1833 min. diff --git a/training/dtrain/examples/parallelized/work/out.0.2 b/training/dtrain/examples/parallelized/work/out.0.2 deleted file mode 100644 index c859db3f..00000000 --- a/training/dtrain/examples/parallelized/work/out.0.2 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.0.0' - output 'work/weights.0.2' - weights in 'work/weights.1' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = -0.1266 - WordPenalty = +0.2244 - LanguageModel = +0.4891 - LanguageModel_OOV = -0.6065 - PhraseModel_0 = -0.634 - PhraseModel_1 = +0.6576 - PhraseModel_2 = +1.165 - PhraseModel_3 = +0.01649 - PhraseModel_4 = -0.8815 - PhraseModel_5 = +0.04098 - PhraseModel_6 = -0.5361 - PassThrough = -0.6292 - --- - 1best avg score: 27.3 (+27.3) - 1best avg model score: +27.47 - avg # updates: 1764 - non-0 feature count: 2824 - avg f count: 153 - avg list sz: 100 -(time 0.1833 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 27.3]. -This took 0.1833 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.0 b/training/dtrain/examples/parallelized/work/out.1.0 deleted file mode 100644 index 7a72e275..00000000 --- a/training/dtrain/examples/parallelized/work/out.1.0 +++ /dev/null @@ -1,44 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.1.0' - output 'work/weights.1.0' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = +0.2684 - WordPenalty = -0.2237 - LanguageModel = -1.104 - LanguageModel_OOV = +0.1174 - PhraseModel_0 = -0.9356 - PhraseModel_1 = -0.9926 - PhraseModel_2 = -0.2008 - PhraseModel_3 = -0.7721 - PhraseModel_4 = +0.5111 - PhraseModel_5 = +0 - PhraseModel_6 = -0.6298 - PassThrough = -0.0118 - --- - 1best avg score: 4.189 (+4.189) - 1best avg model score: +319.9 - avg # updates: 2100 - non-0 feature count: 599 - avg f count: 213.9 - avg list sz: 100 -(time 0.1667 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 4.189]. -This took 0.1667 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.1 b/training/dtrain/examples/parallelized/work/out.1.1 deleted file mode 100644 index bd209601..00000000 --- a/training/dtrain/examples/parallelized/work/out.1.1 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.1.0' - output 'work/weights.1.1' - weights in 'work/weights.0' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = +0.4661 - WordPenalty = +0.07374 - LanguageModel = +0.3354 - LanguageModel_OOV = -0.6514 - PhraseModel_0 = -0.4878 - PhraseModel_1 = +1.085 - PhraseModel_2 = +1.48 - PhraseModel_3 = -0.03441 - PhraseModel_4 = -0.5739 - PhraseModel_5 = +0.1023 - PhraseModel_6 = -0.3455 - PassThrough = -0.3826 - --- - 1best avg score: 10.18 (+10.18) - 1best avg model score: +71.15 - avg # updates: 2121 - non-0 feature count: 2275 - avg f count: 150.8 - avg list sz: 100 -(time 0.15 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 10.18]. -This took 0.15 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.2 b/training/dtrain/examples/parallelized/work/out.1.2 deleted file mode 100644 index f5fc817b..00000000 --- a/training/dtrain/examples/parallelized/work/out.1.2 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.1.0' - output 'work/weights.1.2' - weights in 'work/weights.1' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = +0.3277 - WordPenalty = +0.1759 - LanguageModel = +0.2799 - LanguageModel_OOV = -0.5643 - PhraseModel_0 = -0.7466 - PhraseModel_1 = +0.6823 - PhraseModel_2 = +1.309 - PhraseModel_3 = -0.3185 - PhraseModel_4 = -0.94 - PhraseModel_5 = +0.04098 - PhraseModel_6 = -0.412 - PassThrough = -0.587 - --- - 1best avg score: 13.7 (+13.7) - 1best avg model score: +71.09 - avg # updates: 2223 - non-0 feature count: 2791 - avg f count: 152.8 - avg list sz: 100 -(time 0.15 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 13.7]. -This took 0.15 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.0 b/training/dtrain/examples/parallelized/work/out.2.0 deleted file mode 100644 index 2d27fdc6..00000000 --- a/training/dtrain/examples/parallelized/work/out.2.0 +++ /dev/null @@ -1,44 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.2.0' - output 'work/weights.2.0' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = -0.0099 - WordPenalty = +0.5556 - LanguageModel = +3.129 - LanguageModel_OOV = +0.1064 - PhraseModel_0 = -0.5801 - PhraseModel_1 = -0.3003 - PhraseModel_2 = +0.1759 - PhraseModel_3 = -0.3496 - PhraseModel_4 = -2.562 - PhraseModel_5 = +0.0102 - PhraseModel_6 = -0.4384 - PassThrough = +0.0809 - --- - 1best avg score: 9.987 (+9.987) - 1best avg model score: -102.2 - avg # updates: 1862 - non-0 feature count: 850 - avg f count: 144.5 - avg list sz: 100 -(time 0.2 min, 4 s/S) - ---- -Best iteration: 1 [GOLD = 9.987]. -This took 0.2 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.1 b/training/dtrain/examples/parallelized/work/out.2.1 deleted file mode 100644 index a6cef2b1..00000000 --- a/training/dtrain/examples/parallelized/work/out.2.1 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.2.0' - output 'work/weights.2.1' - weights in 'work/weights.0' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = -0.2622 - WordPenalty = +0.3185 - LanguageModel = +1.89 - LanguageModel_OOV = -0.6097 - PhraseModel_0 = +0.09434 - PhraseModel_1 = +0.2635 - PhraseModel_2 = +0.1182 - PhraseModel_3 = +1.151 - PhraseModel_4 = -0.7466 - PhraseModel_5 = +0.02055 - PhraseModel_6 = -0.3454 - PassThrough = -0.6294 - --- - 1best avg score: 9.998 (+9.998) - 1best avg model score: -27.44 - avg # updates: 1910 - non-0 feature count: 2256 - avg f count: 148.7 - avg list sz: 100 -(time 0.2 min, 4 s/S) - ---- -Best iteration: 1 [GOLD = 9.998]. -This took 0.2 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.2 b/training/dtrain/examples/parallelized/work/out.2.2 deleted file mode 100644 index 908e5214..00000000 --- a/training/dtrain/examples/parallelized/work/out.2.2 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.2.0' - output 'work/weights.2.2' - weights in 'work/weights.1' -(1 dot per processed input) -Iteration #1 of 1. - ... 3 -WEIGHTS - Glue = -0.1781 - WordPenalty = +0.262 - LanguageModel = +1.468 - LanguageModel_OOV = -0.4828 - PhraseModel_0 = -0.4867 - PhraseModel_1 = +0.3306 - PhraseModel_2 = +0.7159 - PhraseModel_3 = +0.01232 - PhraseModel_4 = -1.128 - PhraseModel_5 = +0.04098 - PhraseModel_6 = -0.3829 - PassThrough = -0.5045 - --- - 1best avg score: 16.34 (+16.34) - 1best avg model score: +12.6 - avg # updates: 1823 - non-0 feature count: 2883 - avg f count: 160 - avg list sz: 100 -(time 0.2 min, 4 s/S) - ---- -Best iteration: 1 [GOLD = 16.34]. -This took 0.2 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.0 b/training/dtrain/examples/parallelized/work/out.3.0 deleted file mode 100644 index d2bad0b2..00000000 --- a/training/dtrain/examples/parallelized/work/out.3.0 +++ /dev/null @@ -1,44 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.3.0' - output 'work/weights.3.0' -(1 dot per processed input) -Iteration #1 of 1. - . 1 -WEIGHTS - Glue = -0.081 - WordPenalty = +0.383 - LanguageModel = +1.541 - LanguageModel_OOV = +0.045 - PhraseModel_0 = -0.36 - PhraseModel_1 = -0.4623 - PhraseModel_2 = -0.09999 - PhraseModel_3 = +0.07974 - PhraseModel_4 = -1.442 - PhraseModel_5 = +0.072 - PhraseModel_6 = +0.0898 - PassThrough = +0.009 - --- - 1best avg score: 3.357 (+3.357) - 1best avg model score: +0 - avg # updates: 1699 - non-0 feature count: 564 - avg f count: 206.7 - avg list sz: 100 -(time 0.05 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 3.357]. -This took 0.05 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.1 b/training/dtrain/examples/parallelized/work/out.3.1 deleted file mode 100644 index 3f8c45c4..00000000 --- a/training/dtrain/examples/parallelized/work/out.3.1 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.3.0' - output 'work/weights.3.1' - weights in 'work/weights.0' -(1 dot per processed input) -Iteration #1 of 1. - . 1 -WEIGHTS - Glue = -0.2588 - WordPenalty = +0.2907 - LanguageModel = +1.633 - LanguageModel_OOV = -0.0845 - PhraseModel_0 = -0.3393 - PhraseModel_1 = -0.02459 - PhraseModel_2 = +0.2491 - PhraseModel_3 = +0.07205 - PhraseModel_4 = -0.9481 - PhraseModel_5 = +0.02055 - PhraseModel_6 = -0.2971 - PassThrough = -0.3728 - --- - 1best avg score: 4.499 (+4.499) - 1best avg model score: -45.68 - avg # updates: 2016 - non-0 feature count: 2130 - avg f count: 175.9 - avg list sz: 100 -(time 0.05 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 4.499]. -This took 0.05 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.2 b/training/dtrain/examples/parallelized/work/out.3.2 deleted file mode 100644 index d616560d..00000000 --- a/training/dtrain/examples/parallelized/work/out.3.2 +++ /dev/null @@ -1,45 +0,0 @@ -Loading the LM will be faster if you build a binary file. -Reading ../standard/nc-wmt11.en.srilm.gz -----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 -**************************************************************************************************** - Example feature: Shape_S00000_T00000 -dtrain -Parameters: - k 100 - N 4 - T 1 - learning rate 0.0001 - margin 1 - l1 reg 0 - decoder conf 'cdec.ini' - input 'work/shard.3.0' - output 'work/weights.3.2' - weights in 'work/weights.1' -(1 dot per processed input) -Iteration #1 of 1. - . 1 -WEIGHTS - Glue = +0.2167 - WordPenalty = +0.2738 - LanguageModel = +0.813 - LanguageModel_OOV = -0.6426 - PhraseModel_0 = -0.5211 - PhraseModel_1 = +0.4933 - PhraseModel_2 = +0.9179 - PhraseModel_3 = +0.5142 - PhraseModel_4 = -0.8559 - PhraseModel_5 = +0.03138 - PhraseModel_6 = -0.4129 - PassThrough = -0.6653 - --- - 1best avg score: 21.4 (+21.4) - 1best avg model score: +8.744 - avg # updates: 2287 - non-0 feature count: 2743 - avg f count: 174.8 - avg list sz: 100 -(time 0.05 min, 3 s/S) - ---- -Best iteration: 1 [GOLD = 21.4]. -This took 0.05 min. diff --git a/training/dtrain/examples/parallelized/work/shard.0.0 b/training/dtrain/examples/parallelized/work/shard.0.0 deleted file mode 100644 index a0ef6f54..00000000 --- a/training/dtrain/examples/parallelized/work/shard.0.0 +++ /dev/null @@ -1,3 +0,0 @@ -<seg grammar="grammar/grammar.out.0.gz" id="0">europas nach rassen geteiltes haus</seg> ||| europe 's divided racial house -<seg grammar="grammar/grammar.out.1.gz" id="1">ein gemeinsames merkmal aller extremen rechten in europa ist ihr rassismus und die tatsache , daß sie das einwanderungsproblem als politischen hebel benutzen .</seg> ||| a common feature of europe 's extreme right is its racism and use of the immigration issue as a political wedge . -<seg grammar="grammar/grammar.out.2.gz" id="2">der lega nord in italien , der vlaams block in den niederlanden , die anhänger von le pens nationaler front in frankreich , sind beispiele für parteien oder bewegungen , die sich um das gemeinsame thema : ablehnung der zuwanderung gebildet haben und um forderung nach einer vereinfachten politik , um sie zu regeln .</seg> ||| the lega nord in italy , the vlaams blok in the netherlands , the supporters of le pen 's national front in france , are all examples of parties or movements formed on the common theme of aversion to immigrants and promotion of simplistic policies to control them . diff --git a/training/dtrain/examples/parallelized/work/shard.1.0 b/training/dtrain/examples/parallelized/work/shard.1.0 deleted file mode 100644 index 05f0273b..00000000 --- a/training/dtrain/examples/parallelized/work/shard.1.0 +++ /dev/null @@ -1,3 +0,0 @@ -<seg grammar="grammar/grammar.out.3.gz" id="3">während individuen wie jörg haidar und jean @-@ marie le pen kommen und ( leider nicht zu bald ) wieder gehen mögen , wird die rassenfrage aus der europäischer politik nicht so bald verschwinden .</seg> ||| while individuals like jorg haidar and jean @-@ marie le pen may come and ( never to soon ) go , the race question will not disappear from european politics anytime soon . -<seg grammar="grammar/grammar.out.4.gz" id="4">eine alternde einheimische bevölkerung und immer offenere grenzen vermehren die rassistische zersplitterung in den europäischen ländern .</seg> ||| an aging population at home and ever more open borders imply increasing racial fragmentation in european countries . -<seg grammar="grammar/grammar.out.5.gz" id="5">die großen parteien der rechten und der linken mitte haben sich dem problem gestellt , in dem sie den kopf in den sand gesteckt und allen aussichten zuwider gehofft haben , es möge bald verschwinden .</seg> ||| mainstream parties of the center left and center right have confronted this prospect by hiding their heads in the ground , hoping against hope that the problem will disappear . diff --git a/training/dtrain/examples/parallelized/work/shard.2.0 b/training/dtrain/examples/parallelized/work/shard.2.0 deleted file mode 100644 index 0528d357..00000000 --- a/training/dtrain/examples/parallelized/work/shard.2.0 +++ /dev/null @@ -1,3 +0,0 @@ -<seg grammar="grammar/grammar.out.6.gz" id="6">das aber wird es nicht , wie die geschichte des rassismus in amerika deutlich zeigt .</seg> ||| it will not , as america 's racial history clearly shows . -<seg grammar="grammar/grammar.out.7.gz" id="7">die beziehungen zwischen den rassen standen in den usa über jahrzehnte - und tun das noch heute - im zentrum der politischen debatte . das ging so weit , daß rassentrennung genauso wichtig wie das einkommen wurde , - wenn nicht sogar noch wichtiger - um politische zuneigungen und einstellungen zu bestimmen .</seg> ||| race relations in the us have been for decades - and remain - at the center of political debate , to the point that racial cleavages are as important as income , if not more , as determinants of political preferences and attitudes . -<seg grammar="grammar/grammar.out.8.gz" id="8">der erste schritt , um mit der rassenfrage umzugehen ist , ursache und folgen rassistischer feindseligkeiten zu verstehen , auch dann , wenn das bedeutet , unangenehme tatsachen aufzudecken .</seg> ||| the first step to address racial politics is to understand the origin and consequences of racial animosity , even if it means uncovering unpleasant truths . diff --git a/training/dtrain/examples/parallelized/work/shard.3.0 b/training/dtrain/examples/parallelized/work/shard.3.0 deleted file mode 100644 index f7cbb3e3..00000000 --- a/training/dtrain/examples/parallelized/work/shard.3.0 +++ /dev/null @@ -1 +0,0 @@ -<seg grammar="grammar/grammar.out.9.gz" id="9">genau das haben in den usa eine große anzahl an forschungsvorhaben in wirtschaft , soziologie , psychologie und politikwissenschaft geleistet . diese forschungen zeigten , daß menschen unterschiedlicher rasse einander deutlich weniger vertrauen .</seg> ||| this is precisely what a large amount of research in economics , sociology , psychology and political science has done for the us . diff --git a/training/dtrain/examples/parallelized/work/weights.0 b/training/dtrain/examples/parallelized/work/weights.0 deleted file mode 100644 index 560bab86..00000000 --- a/training/dtrain/examples/parallelized/work/weights.0 +++ /dev/null @@ -1,2072 +0,0 @@ -LanguageModel 1.0461718569464984 -PhraseModel_4 -0.9877757214580491 -PhraseModel_1 -0.27641632310025577 -PhraseModel_0 -0.5640090252696333 -PhraseModel_2 0.20626506994462934 -PhraseModel_3 -0.38409074694928547 -PhraseModel_6 -0.31797499999999995 -WordPenalty 0.1940427745143702 -RBT:X1_</r> -0.16625 -RBS:<r>_X -0.14205 -RBT:X2_</r> 0.08432500000000001 -Shape_S10000_T10000 -0.0010500000000000023 -RBS:X_</r> -0.010700000000000005 -RBT:<r>_X1 0.041625000000000016 -R:S:NS_NX:N1_N2 0.093975 -RBT:S1_X2 0.093975 -RBT:<r>_S1 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0.0032000000000000002 -RBT:<r>_created 0.0028 -RBS:X_haben -0.0094000000000000004 -R:X:NX_haben:N1_, -0.0097999999999999997 -R:X:NX_haben:have_N1 0.00040000000000000002 -R:X:NX_gebildet:created_N1 0.0028 -R:X:NX_gebildet:formed_N1 -0.015800000000000002 -R:X:NX_gebildet:up_N1 0.00040000000000000002 -R:X:NX_gebildet:established_N1 0.0032000000000000002 -R:X:NX_gebildet_NX:N2_formed_N1 0.0094000000000000004 diff --git a/training/dtrain/examples/parallelized/work/weights.1 b/training/dtrain/examples/parallelized/work/weights.1 deleted file mode 100644 index 270dbb59..00000000 --- a/training/dtrain/examples/parallelized/work/weights.1 +++ /dev/null @@ -1,2641 +0,0 @@ -LanguageModel 1.1008595900906253 -PhraseModel_2 0.804224437304719 -PhraseModel_1 0.6242269758630035 -PhraseModel_4 -0.7781209969878504 -PhraseModel_3 0.34257722211028796 -LanguageModel_OOV -0.494175 -PassThrough -0.5169 -PhraseModel_6 -0.341825 -PhraseModel_0 -0.2564652741416422 -Shape_S01010_T01010 0.007300000000000015 -RBT:S1_X2 0.007300000000000015 -R:S:NS_NX:N1_N2 0.007300000000000015 -RBT:<r>_S1 0.007300000000000015 -RBS:<r>_S 0.007300000000000015 -Glue 0.007300000000000015 -RBS:S_X 0.007300000000000015 -Shape_S10000_T10000 -0.11412499999999999 -RBS:X_</r> -0.08339999999999999 -RBT:X2_</r> 0.007075000000000033 -WordPenalty 0.21258714889163938 -RBT:X1_</r> -0.1372 -RBS:<r>_X -0.12465 -RBT:of_</r> 0.1007 -RBT:<r>_against 0.0555 -RBT:against_</r> 0.0555 -R:X:zuwider:against 0.0555 -RBT:<r>_of 0.04062500000000001 -RBT:<r>_the -0.08017500000000002 -RBT:the_</r> -0.076675 -RBT:<r>_and 0.072 -RBT:X1_X2 -0.06735000000000001 -RBT:countries_</r> 0.059075 -RBT:and_</r> 0.079425 -RBT:as_</r> 0.04820000000000001 -RBT:und_</r> -0.06052500000000001 -R:X:und:und -0.06052500000000001 -RBT:<r>_und -0.06052500000000001 -RBT:<r>_europe 0.059500000000000004 -RBT:,_X1 -0.0626 -Shape_S01110_T11110 -0.07705 -RBS:die_</r> -0.06860000000000001 -R:X:für:for -0.05697500000000001 -R:X:für:of 0.05697500000000001 -RBT:europe_</r> 0.052425000000000006 -RBT:ländern_</r> -0.04187500000000001 -RBT:<r>_ländern -0.04187500000000001 -R:X:ländern:ländern -0.04187500000000001 -RBT:<r>_for -0.0567 -RBT:<r>_X1 0.04132500000000002 -RBT:a_X1 -0.070925 -RBT:X1_, 0.0664 -RBT:zuwider_</r> -0.0335 -R:X:zuwider:zuwider -0.0335 -RBT:<r>_zuwider -0.0335 -R:X:ländern:countries 0.033375 -RBT:<r>_countries 0.033375 -Shape_S01100_T01100 0.005574999999999993 -R:X:und:and 0.060325000000000004 -RBT:<r>_europas -0.031525000000000004 -RBT:europas_</r> -0.031525000000000004 -R:X:europas:europas -0.031525000000000004 -RBT:<r>_as 0.044675000000000006 -RBT:<r>_us 0.042575 -Shape_S01111_T01011 -0.04895 -RBS:,_</r> -0.05367500000000001 -Shape_S11000_T11000 -0.05635000000000002 -RBT:<r>_be -0.059800000000000006 -R:X:europas:europe 0.04055 -RBT:<r>_marie 0.044475 -R:X:marie:marie 0.044475 -RBT:marie_</r> 0.044475 -RBT:<r>_even -0.039525000000000005 -Shape_S01100_T11000 -0.035225 -RBT:,_</r> 0.02045 -R:X:europäischen:europäischen -0.039575 -RBT:<r>_europäischen -0.039575 -RBT:europäischen_</r> -0.039575 -RBT:'s_</r> 0.037725 -RBT:racism_</r> 0.046625000000000014 -PhraseModel_5 0.040975000000000004 -RBS:nicht_</r> -0.031225000000000003 -RBT:for_</r> -0.028449999999999996 -RBT:in_</r> -0.031700000000000006 -R:X:wie:as 0.025625000000000002 -RBT:usa_</r> -0.02645 -R:X:usa:usa -0.02645 -RBT:<r>_usa -0.02645 -RBS:zu_</r> 0.004425 -R:X:zu:to 0.004425 -RBS:noch_wichtiger 0.027274999999999997 -RBS:<r>_wichtiger -0.027274999999999997 -R:X:noch_wichtiger:more 0.027274999999999997 -RBS:<r>_sogar -0.027174999999999998 -RBS:nicht_sogar 0.027174999999999998 -RBS:<r>_zu 0.004024999999999999 -RBT:<r>_lega 0.04190000000000001 -RBT:nord_</r> 0.04190000000000001 -RBT:<r>_nord 0.04190000000000001 -R:X:nord:nord 0.04190000000000001 -RBS:lega_</r> 0.04190000000000001 -R:X:lega:lega 0.04190000000000001 -RBT:lega_</r> 0.04190000000000001 -RBT:<r>_northern -0.04190000000000001 -RBS:lega_X -0.04190000000000001 -RBT:X1_league -0.04190000000000001 -R:X:lega_NX:N1_league -0.04190000000000001 -R:X:nord:northern -0.04190000000000001 -RBT:northern_</r> -0.04190000000000001 -RBT:league_</r> -0.04190000000000001 -RBT:-_</r> -0.031825 -RBS:X_zu -0.0036749999999999994 -RBT:<r>_have 0.049249999999999995 -RBT:even_</r> -0.024475 -R:X:nicht_sogar:not 0.024475 -RBT:in_the 0.04882500000000001 -RBS:in_</r> -0.03345 -R:X:europäischen:european 0.02415 -RBS:noch_</r> -0.0231 -RBS:<r>_in -0.03515 -RBT:is_</r> -0.047200000000000006 -RBT:us_X1 0.035074999999999995 -RBS:X_in 0.032900000000000006 -RBT:<r>_history 0.0439 -RBT:is_intended -0.0463 -RBT:intended_X2 -0.0463 -RBT:ensure_X1 -0.0463 -RBT:X2_ensure -0.0463 -RBT:which_is -0.0463 -R:X:NX_dem_NX:which_is_intended_N2_ensure_N1 -0.0463 -RBS:und_</r> -0.027324999999999995 -RBT:<r>_more 0.02505 -RBS:<r>_noch 0.02505 -RBT:more_</r> 0.02505 -RBT:wichtiger_</r> -0.02505 -R:X:wichtiger:wichtiger -0.02505 -RBT:<r>_wichtiger -0.02505 -RBT:<r>_european 0.016024999999999998 -RBT:wie_</r> -0.009600000000000003 -RBT:<r>_wie -0.009600000000000003 -R:X:wie:wie -0.009600000000000003 -RBS:X_@-@ 0.02255 -RBS:jean_</r> 0.02255 -R:X:aller:aller -0.022500000000000003 -R:X:aller:of 0.022500000000000003 -R:X:merkmal:feature 0.022500000000000003 -RBT:<r>_feature 0.022500000000000003 -RBT:<r>_aller -0.022500000000000003 -RBT:feature_</r> 0.022500000000000003 -RBT:<r>_merkmal -0.022500000000000003 -RBT:jean_@-@ 0.045000000000000005 -RBT:aller_</r> -0.022500000000000003 -RBT:merkmal_</r> -0.022500000000000003 -R:X:merkmal:merkmal -0.022500000000000003 -RBT:within_</r> 0.0447 -RBT:european_</r> 0.00825 -R:X:-:- -0.022250000000000002 -R:X:-:, 0.022250000000000002 -R:X:sogar_noch:even -0.022250000000000002 -RBS:sogar_noch -0.022250000000000002 -RBT:its_choices 0.0444 -RBT:make_its 0.0444 -RBT:count_in 0.0444 -R:X:NX_dem_NX_in:N1_make_its_choices_count_in_the_N2_,_within 0.0444 -RBT:being_attracted -0.0444 -RBT:attracted_into -0.0444 -RBT:X1_make 0.0444 -R:X:NX_in:N1_being_attracted_into -0.0444 -RBT:choices_count 0.0444 -RBT:,_within 0.0444 -RBT:X1_being -0.0444 -RBT:into_</r> -0.04415 -RBS:marie_</r> 0.021975 -R:X:le:le 0.021975 -RBS:<r>_le 0.021975 -RBS:<r>_marie 0.021975 -RBT:<r>_pen 0.021975 -RBS:marie_le -0.021975 -RBS:@-@_marie -0.021975 -R:X:jean_@-@_marie_le_pen:le_pen -0.021975 -R:X:pen:pen 0.021975 -RBT:le_</r> 0.021975 -RBS:le_</r> 0.021975 -R:X:nicht:nicht -0.021575 -RBT:nicht_</r> -0.021575 -RBT:<r>_nicht -0.021575 -RBS:X_wie -0.043750000000000004 -RBT:<r>_is -0.037774999999999996 -RBS:die_X 0.040575 -RBS:<r>_das -0.038125000000000006 -RBS:sogar_</r> 0.019450000000000005 -R:X:in:in -0.0266 -RBS:wird_</r> -0.037125000000000005 -R:X:aber:is -0.041675000000000004 -RBT:X2_for -0.041675000000000004 -RBT:<r>_what -0.041675000000000004 -RBT:X1_history -0.041675000000000004 -RBT:example_the -0.041675000000000004 -R:X:wird:be -0.041675000000000004 -RBT:for_example -0.041675000000000004 -RBT:for_a -0.041675000000000004 -R:X:das:what -0.041675000000000004 -R:X:NX_geschichte_NX:N2_for_a_N1_history -0.041675000000000004 -R:X:NX_wie_die:N1_for_example_the -0.041675000000000004 -RBT:what_</r> -0.041675000000000004 -RBT:when_</r> -0.041425 -RBS:X_geschichte -0.041325 -RBT:the_united -0.041325 -RBS:den_</r> -0.0281 -RBT:ahead_X1 0.0409 -RBT:gone_ahead 0.0409 -RBT:have_gone 0.0409 -RBT:experience_in -0.0409 -RBT:in_connection -0.0409 -R:X:NX_haben:have_gone_ahead_N1 0.0409 -RBT:<r>_experience -0.0409 -R:X:NX_haben:experience_in_connection_N1 -0.0409 -RBT:connection_X1 -0.0409 -RBS:und_jean 0.020425000000000002 -RBS:<r>_jean -0.020425000000000002 -R:X:und_jean:and_jean 0.020425000000000002 -RBT:and_jean 0.020425000000000002 -RBS:haidar_</r> -0.020425000000000002 -RBT:haider_X1 0.020425000000000002 -Shape_S11100_T11000 0.020425000000000002 -RBS:haidar_X 0.020425000000000002 -RBT:<r>_haider 0.020425000000000002 -R:X:haidar_NX_@-@:haider_N1 0.020425000000000002 -RBT:haidar_</r> -0.020425000000000002 -R:X:haidar:haidar -0.020425000000000002 -RBT:<r>_haidar -0.020425000000000002 -RBT:X1_for -0.040625 -RBT:X2_, 0.04045 -RBT:extreme_</r> 0.02025 -RBT:extremen_</r> -0.02025 -RBT:<r>_extreme 0.02025 -R:X:extremen:extreme 0.02025 -RBT:<r>_extremen -0.02025 -R:X:extremen:extremen -0.02025 -RBT:<r>_X2 -0.0403 -R:X:nicht:not -0.020075 -RBT:<r>_in -0.020875 -R:X:zuwider:to -0.02 -RBT:the_X1 -0.039125 -RBT:to_</r> -0.03950000000000001 -RBS:@-@_</r> 0.01985 -RBS:zu_X -0.019299999999999994 -RBT:X1_the -0.03875 -RBS:<r>_) 0.019275 -RBS:X_) -0.019275 -R:X:):) 0.019275 -RBT:X2_) -0.019225000000000003 -R:X:NX_zu_NX_):N1_N2_) -0.019225000000000003 -RBT:<r>_racial 0.037700000000000004 -RBT:the_X2 0.038025 -RBT:<r>_racism 0.022000000000000006 -RBT:<r>_- -0.0010250000000000016 -RBT:le_pen 0.0005250000000000029 -RBS:<r>_pen -0.0005250000000000029 -RBS:jean_@-@ 0.0005250000000000029 -RBT:jean_</r> -0.0005250000000000029 -RBS:le_pen 0.0005250000000000029 -Shape_S01110_T01110 0.03715 -RBT:<r>_do 0.036800000000000006 -RBS:<r>_usa -0.022025000000000003 -RBS:aber_</r> -0.037450000000000004 -R:X:rassismus:racism 0.020425 -R:X:geschichte:geschichte -0.01855 -RBT:geschichte_</r> -0.01855 -RBT:<r>_geschichte -0.01855 -RBT:history_</r> -0.0353 -RBT:if_</r> 0.035175000000000005 -RBS:in_den 0.020225 -RBS:es_nicht 0.020500000000000004 -RBS:rassenfrage_X 0.03225 -RBS:rassenfrage_</r> -0.03225 -RBS:X_, -0.0025999999999999947 -R:X:.:, -0.036275 -RBS:deutlich_</r> 0.0361 -RBT:<r>_it 0.031125 -RBT:<r>_political 0.03242500000000001 -RBT:rassismus_</r> -0.017799999999999996 -RBT:<r>_rassismus -0.017799999999999996 -R:X:rassismus:rassismus -0.017799999999999996 -RBT:<r>_racist -0.03465 -RBT:people_X1 0.035824999999999996 -RBT:not_</r> 0.010675 -R:X:pens:pen_'s 0.017875000000000002 -RBT:pen_'s 0.017875000000000002 -R:X:pens:pen -0.017875000000000002 -RBS:den_usa 0.017525000000000002 -R:X:den:the -0.0173 -RBS:<r>_wird -0.03370000000000001 -RBS:geteiltes_X 0.032775 -RBS:geteiltes_</r> -0.032775 -RBT:<r>_there -0.033800000000000004 -RBT:._</r> -0.0338 -RBT:<r>_) -0.003225000000000004 -RBT:it_</r> 0.0321 -RBT:<r>_people 0.03315 -RBS:die_geschichte 0.02135 -R:X:NX_auch_dann_,_wenn:N1_in -0.016225000000000003 -R:X:NX_in_den_usa:us_N1 0.016175000000000002 -RBT:<r>_at -0.03217500000000001 -RBT:united_states -0.031950000000000006 -RBT:divided_</r> 0.022125000000000002 -RBS:es_X -0.018225 -RBT:rechten_</r> -0.0159 -R:X:rechten:rechten -0.0159 -RBT:<r>_rechten -0.0159 -RBS:<r>_geschichte 0.019975 -RBS:,_wie 0.031525 -R:X:rechten:right 0.01575 -RBT:<r>_right 0.01575 -RBT:right_</r> 0.01575 -R:X:es_NX:people_N1 0.031325 -RBT:X1_if 0.029625 -RBT:pen_</r> 0.0046250000000000015 -RBS:bestimmen_. 0.015600000000000001 -RBS:<r>_bestimmen -0.015600000000000001 -RBT:<r>_bestimmen -0.015600000000000001 -RBT:bestimmen_</r> -0.015600000000000001 -R:X:bestimmen:bestimmen -0.015600000000000001 -RBS:zu_bestimmen 0.015600000000000001 -RBS:bestimmen_</r> -0.015600000000000001 -R:X:NX_zu_bestimmen_.:N1_. 0.0155 -RBT:<r>_will 0.02275 -RBT:of_X1 -0.03095 -RBT:X1_. 0.01525 -Shape_S11000_T01100 0.0274 -RBS:auch_dann -0.015275 -RBS:X_dann 0.015275 -R:X:NX_dann_,_wenn:N1_in 0.015275 -RBS:auch_</r> 0.015275 -R:X:,_wie_die_NX:N1_,_and 0.03045 -RBS:<r>_nicht 0.001825000000000001 -RBT:<r>_those 0.030100000000000002 -RBS:<r>_den 0.002650000000000003 -RBS:an_X 0.028325000000000003 -RBS:an_</r> -0.028325000000000003 -RBT:<r>_. -0.01315 -RBT:,_and 0.029875000000000002 -RBT:do_not 0.029825000000000004 -RBT:will_soon 0.02925 -R:X:in:when -0.02925 -R:X:des_NX:of_a_N1 -0.02925 -RBT:states_X2 -0.02925 -RBT:racist_action -0.02925 -R:X:NX_amerika_NX_.:N1_the_united_states_N2_. -0.02925 -RBT:action_X1 -0.02925 -R:X:rassismus_NX:racist_action_N1 -0.02925 -RBS:-_X -0.029175000000000003 -RBT:<r>_that -0.023225000000000003 -RBT:<r>_when -0.029150000000000002 -Shape_S11110_T11010 -0.01525 -RBS:<r>_. -0.010350000000000003 -RBT:is_, -0.028900000000000002 -R:X:es_NX:there_is_,_N1 -0.028900000000000002 -RBT:there_is 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