Difference between revisions of "Kaingang and Portuguese/Structural Transfer"
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[[Category:Sp19_StructuralTransfer]] [[Category:Kaingang]] [[Category:Portuguese]] | [[Category:Sp19_StructuralTransfer]] [[Category:Kaingang]] [[Category:Portuguese]] | ||
==Pre-evaluation== | ==Pre-evaluation== | ||
| − | *'''WER:''' | + | Statistics about input files |
| − | *'''PER:''' | + | ------------------------------------------------------- |
| + | Number of words in reference: 63 | ||
| + | Number of words in test: 63 | ||
| + | Number of unknown words (marked with a star) in test: 26 | ||
| + | Percentage of unknown words: 41.27 % | ||
| + | |||
| + | Results when removing unknown-word marks (stars) | ||
| + | ------------------------------------------------------- | ||
| + | Edit distance: 38 | ||
| + | Word error rate (WER): 60.32 % | ||
| + | Number of position-independent correct words: 25 | ||
| + | Position-independent word error rate (PER): 60.32 % | ||
| + | |||
| + | Results when unknown-word marks (stars) are not removed | ||
| + | ------------------------------------------------------- | ||
| + | Edit distance: 63 | ||
| + | Word Error Rate (WER): 100.00 % | ||
| + | Number of position-independent correct words: 0 | ||
| + | Position-independent word error rate (PER): 100.00 % | ||
| + | |||
| + | Statistics about the translation of unknown words | ||
| + | ------------------------------------------------------- | ||
| + | Number of unknown words which were free rides: 25 | ||
| + | Percentage of unknown words that were free rides: 96.15 % | ||
| + | |||
| + | *'''WER:''' 60.32% | ||
| + | |||
| + | *'''PER:''' 60.32% | ||
| + | |||
*'''Coverage:''' | *'''Coverage:''' | ||
| − | == | + | $ aq-covtest ling073-kgp-por-corpus/kgp.tests.txt ling073-kgp-por/kgp-por.automorf.bin |
| − | '''Sentence:''' | + | Number of tokenised words in the corpus: 82 |
| + | Coverage: 64.63% | ||
| + | Top unknown words in the corpus: | ||
| + | 3 vỹ | ||
| + | 2 fi | ||
| + | 1 kafã | ||
| + | 1 Nũgnũj | ||
| + | 1 kur | ||
| + | 1 ẽgno | ||
| + | 1 tũg | ||
| + | 1 São | ||
| + | 1 Pau | ||
| + | 1 o | ||
| + | 1 rã | ||
| + | 1 jur | ||
| + | 1 tá | ||
| + | 1 Téj | ||
| + | 1 ki | ||
| + | 1 panh | ||
| + | 1 kãfór | ||
| + | 1 kyrũ | ||
| + | 1 jãmré | ||
| + | 1 ũn | ||
| + | Translation time: 0.0028295516967773438 seconds | ||
| + | ==Example for implementation== | ||
| + | '''Sentence:''' | ||
| + | “Inh kã’u ã,” he tóg. “Inh mỹ ã tóg tỹ, ũ nĩ ven nĩ vẽ, hã ra ã tóg tỹ, ã hã nĩ”, he tóg. | ||
| + | |||
| + | '''Portuguese Translation:''' | ||
| + | “Você me assustou, pensei que você era um outro mas é você mesmo”, ele falou para mim. | ||
| − | '''Tagger output:''' | + | '''Tagger output:''' |
| + | “^Inh/inh<prn><pes>/inh<prn><p1><sg>$ ^kã’u/kã’u<v><tv>$ ^ã/ã<prn>/ã<prn><p2><sg>$^,/,<cm>$” ^he/he<v><tv>$ ^tóg/tóg<su>$^./.<sent>$ “^Inh/inh<prn><pes>/inh<prn><p1><sg>$ ^mỹ/mỹ<cir>$ ^ã/ã<prn>/ã<prn><p2><sg>$ ^tóg/tóg<su>$ ^tỹ/tỹ<cir>$^,/,<cm>$ ^ũ/ũ<prn>$ ^nĩ/nĩ<a>/nĩ<n>/nĩ<v><iv><sg>$ ^ven/ven<v><tv><sg>$ ^nĩ/nĩ<a>/nĩ<n>/nĩ<v><iv><sg>$ ^vẽ/vẽ<a>$^,/,<cm>$ ^hã/hã<o>$ ^ra/ra<cir>$ ^ã/ã<prn>/ã<prn><p2><sg>$ ^tóg/tóg<su>$ ^tỹ/tỹ<cir>$^,/,<cm>$ ^ã/ã<prn>/ã<prn><p2><sg>$ ^hã/hã<o>$ ^nĩ/nĩ<a>/nĩ<n>/nĩ<v><iv><sg>$”^,/,<cm>$ ^he/he<v><tv>$ ^tóg/tóg<su>$^./.<sent>$^./.<sent>$ | ||
| − | '''Biltrans output:''' | + | '''Biltrans output:''' |
| + | “^Inh<prn><pes>/Eu<prn><tn><pes>/Meu<prn><tn><pes>/De mim<prn><tn><pes>$ ^kã’u<v><tv>/assustar<vblex>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$^,<cm>/,<cm>$” ^he<v><tv>/dizer<vblex>$ ^tóg<su>/ele<prn><tn>$^.<sent>/.<sent>$ “^Inh<prn><pes>/Eu<prn><tn><pes>/Meu<prn><tn><pes>/De mim<prn><tn><pes>$ ^mỹ<cir>/para<pr>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$ ^tóg<su>/ele<prn><tn>$ ^tỹ<cir>/por<pr>/com<pr>$^,<cm>/,<cm>$ ^ũ<prn>/alguém<prn><tn>$ ^nĩ<a>/no momento<adv>$ ^ven<v><tv><sg>/mostrar<vblex>$ ^nĩ<a>/no momento<adv>$ ^vẽ<a>/é<vblex>/era<vblex>/ser<vblex>$^,<cm>/,<cm>$ ^hã<o>/igual<adj>/parecido<adj>$ ^ra<cir>/para<pr>/apesar do<cnjadv>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$ ^tóg<su>/ele<prn><tn>$ ^tỹ<cir>/por<pr>/com<pr>$^,<cm>/,<cm>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$ ^hã<o>/igual<adj>/parecido<adj>$ ^nĩ<a>/no momento<adv>$”^,<cm>/,<cm>$ ^he<v><tv>/dizer<vblex>$ ^tóg<su>/ele<prn><tn>$^.<sent>/.<sent>$^.<sent>/.<sent> | ||
'''Chunker output:''' | '''Chunker output:''' | ||
| + | apertium-transfer: Rule 1 .<sent>/.<sent> | ||
| + | apertium-transfer: Rule 2 mỹ<cir>/para<pr> | ||
| + | apertium-transfer: Rule 3 ã<prn>/tu<prn><tn><p2><mf><sg> tóg<su>/ele<prn><tn> | ||
| + | apertium-transfer: Rule 2 tỹ<cir>/por<pr>/com<pr> | ||
| + | apertium-transfer: Rule 2 ra<cir>/para<pr>/apesar do<cnjadv> | ||
| + | apertium-transfer: Rule 3 ã<prn>/tu<prn><tn><p2><mf><sg> tóg<su>/ele<prn><tn> | ||
| + | apertium-transfer: Rule 2 tỹ<cir>/por<pr>/com<pr> | ||
| + | apertium-transfer: Rule 1 .<sent>/.<sent> | ||
| + | apertium-transfer: Rule 1 .<sent>/.<sent> | ||
| + | “^default<default>{^Eu<prn><tn><pes>$}$ ^default<default>{^assustar<vblex>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$^default<default>{^,<cm>$}$” ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$ “^default<default>{^Eu<prn><tn><pes>$}$ ^pr<SP>{^para<pr>$}$ ^prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$}$ ^pr<SP>{^por<pr>$}$^default<default>{^,<cm>$}$ ^default<default>{^alguém<prn><tn>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^mostrar<vblex>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^é<vblex>$}$^default<default>{^,<cm>$}$ ^default<default>{^igual<adj>$}$ ^pr<SP>{^para<pr>$}$ ^prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$}$ ^pr<SP>{^por<pr>$}$^default<default>{^,<cm>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$ ^default<default>{^igual<adj>$}$ ^default<default>{^no momento<adv>$}$”^default<default>{^,<cm>$}$ ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$^sent<SENT>{^.<sent>$}$ | ||
'''Interchunk output:''' | '''Interchunk output:''' | ||
| + | apertium-interchunk: Rule 1 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$} | ||
| + | apertium-interchunk: Rule 2 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$} pr<SP>{^por<pr>$} | ||
| + | apertium-interchunk: Rule 1 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$} | ||
| + | apertium-interchunk: Rule 2 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$} pr<SP>{^por<pr>$} | ||
| + | “^default<default>{^Eu<prn><tn><pes>$}$ ^default<default>{^assustar<vblex>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$^default<default>{^,<cm>$}$” ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$ “^default<default>{^Eu<prn><tn><pes>$}$ ^pr<SP>{^para<pr>$}$ ^pr<SP>{^por<pr>$}$ ^prn<SN><obj>{^tu<prn><tn><p2><mf><sg><2>$}$^default<default>{^,<cm>$}$ ^default<default>{^alguém<prn><tn>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^mostrar<vblex>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^é<vblex>$}$^default<default>{^,<cm>$}$ ^default<default>{^igual<adj>$}$ ^pr<SP>{^para<pr>$}$ ^pr<SP>{^por<pr>$}$ ^prn<SN><obj>{^tu<prn><tn><p2><mf><sg><2>$}$^default<default>{^,<cm>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$ ^default<default>{^igual<adj>$}$ ^default<default>{^no momento<adv>$}$”^default<default>{^,<cm>$}$ ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$^sent<SENT>{^.<sent>$}$ | ||
'''Postchunk output:''' | '''Postchunk output:''' | ||
| + | “^Eu<prn><tn><pes>$ ^assustar<vblex>$ ^tu<prn><tn><p2><mf><sg>$^,<cm>$” ^dizer<vblex>$ ^ele<prn><tn>$^.<sent>$ “^Eu<prn><tn><pes>$ ^para<pr>$ ^por<pr>$ ^tu<prn><tn><p2><mf><sg><obj>$^,<cm>$ ^alguém<prn><tn>$ ^no momento<adv>$ ^mostrar<vblex>$ ^no momento<adv>$ ^é<vblex>$^,<cm>$ ^igual<adj>$ ^para<pr>$ ^por<pr>$ ^tu<prn><tn><p2><mf><sg><obj>$^,<cm>$ ^tu<prn><tn><p2><mf><sg>$ ^igual<adj>$ ^no momento<adv>$”^,<cm>$ ^dizer<vblex>$ ^ele<prn><tn>$^.<sent>$^.<sent>$ | ||
'''kgp-por output:''' | '''kgp-por output:''' | ||
| + | “#Eu #assustar #tu,” #dizer #ele. “#Eu para por ti, #alguém #no momento #mostrar #no momento #é, #igual para por ti, #tu #igual #no momento”, #dizer #ele. | ||
==Post-evaluation== | ==Post-evaluation== | ||
| − | *'''WER:''' | + | $ apertium-eval-translator -r ../tools/kgp.tests.txt -t ../ling073-kgp-por/kgp-por.tests.txt |
| − | *'''PER:''' | + | Test file: '../ling073-kgp-por/kgp-por.tests.txt' |
| + | Reference file '../tools/kgp.tests.txt' | ||
| + | |||
| + | Statistics about input files | ||
| + | ------------------------------------------------------- | ||
| + | Number of words in reference: 63 | ||
| + | Number of words in test: 73 | ||
| + | Number of unknown words (marked with a star) in test: | ||
| + | Percentage of unknown words: 0.00 % | ||
| + | |||
| + | Results when removing unknown-word marks (stars) | ||
| + | ------------------------------------------------------- | ||
| + | Edit distance: 72 | ||
| + | Word error rate (WER): 114.29 % | ||
| + | Number of position-independent correct words: 1 | ||
| + | Position-independent word error rate (PER): 114.29 % | ||
| + | |||
| + | Results when unknown-word marks (stars) are not removed | ||
| + | ------------------------------------------------------- | ||
| + | Edit distance: 72 | ||
| + | Word Error Rate (WER): 114.29 % | ||
| + | Number of position-independent correct words: 1 | ||
| + | Position-independent word error rate (PER): 114.29 % | ||
| + | |||
| + | Statistics about the translation of unknown words | ||
| + | ------------------------------------------------------- | ||
| + | Number of unknown words which were free rides: 0 | ||
| + | Percentage of unknown words that were free rides: 0% | ||
| + | *'''WER:''' 114.29 % ??? | ||
| + | *'''PER:''' 114.29 % ??? | ||
*'''Coverage:''' | *'''Coverage:''' | ||
| + | $ aq-covtest ling073-kgp-por-corpus/kgp.tests.txt ling073-kgp-por/kgp-por.automorf.bin | ||
| + | Number of tokenised words in the corpus: 80 | ||
| + | Coverage: 100.00% | ||
| + | Top unknown words in the corpus: | ||
| + | Translation time: 0.002888202667236328 seconds | ||
Latest revision as of 15:16, 19 April 2019
Pre-evaluation
Statistics about input files ------------------------------------------------------- Number of words in reference: 63 Number of words in test: 63 Number of unknown words (marked with a star) in test: 26 Percentage of unknown words: 41.27 % Results when removing unknown-word marks (stars) ------------------------------------------------------- Edit distance: 38 Word error rate (WER): 60.32 % Number of position-independent correct words: 25 Position-independent word error rate (PER): 60.32 % Results when unknown-word marks (stars) are not removed ------------------------------------------------------- Edit distance: 63 Word Error Rate (WER): 100.00 % Number of position-independent correct words: 0 Position-independent word error rate (PER): 100.00 %
Statistics about the translation of unknown words ------------------------------------------------------- Number of unknown words which were free rides: 25 Percentage of unknown words that were free rides: 96.15 %
- WER: 60.32%
- PER: 60.32%
- Coverage:
$ aq-covtest ling073-kgp-por-corpus/kgp.tests.txt ling073-kgp-por/kgp-por.automorf.bin Number of tokenised words in the corpus: 82 Coverage: 64.63% Top unknown words in the corpus: 3 vỹ 2 fi 1 kafã 1 Nũgnũj 1 kur 1 ẽgno 1 tũg 1 São 1 Pau 1 o 1 rã 1 jur 1 tá 1 Téj 1 ki 1 panh 1 kãfór 1 kyrũ 1 jãmré 1 ũn Translation time: 0.0028295516967773438 seconds
Example for implementation
Sentence:
“Inh kã’u ã,” he tóg. “Inh mỹ ã tóg tỹ, ũ nĩ ven nĩ vẽ, hã ra ã tóg tỹ, ã hã nĩ”, he tóg.
Portuguese Translation:
“Você me assustou, pensei que você era um outro mas é você mesmo”, ele falou para mim.
Tagger output:
“^Inh/inh<prn><pes>/inh<prn><p1><sg>$ ^kã’u/kã’u<v><tv>$ ^ã/ã<prn>/ã<prn><p2><sg>$^,/,<cm>$” ^he/he<v><tv>$ ^tóg/tóg<su>$^./.<sent>$ “^Inh/inh<prn><pes>/inh<prn><p1><sg>$ ^mỹ/mỹ<cir>$ ^ã/ã<prn>/ã<prn><p2><sg>$ ^tóg/tóg<su>$ ^tỹ/tỹ<cir>$^,/,<cm>$ ^ũ/ũ<prn>$ ^nĩ/nĩ<a>/nĩ<n>/nĩ<v><iv><sg>$ ^ven/ven<v><tv><sg>$ ^nĩ/nĩ<a>/nĩ<n>/nĩ<v><iv><sg>$ ^vẽ/vẽ<a>$^,/,<cm>$ ^hã/hã<o>$ ^ra/ra<cir>$ ^ã/ã<prn>/ã<prn><p2><sg>$ ^tóg/tóg<su>$ ^tỹ/tỹ<cir>$^,/,<cm>$ ^ã/ã<prn>/ã<prn><p2><sg>$ ^hã/hã<o>$ ^nĩ/nĩ<a>/nĩ<n>/nĩ<v><iv><sg>$”^,/,<cm>$ ^he/he<v><tv>$ ^tóg/tóg<su>$^./.<sent>$^./.<sent>$
Biltrans output:
“^Inh<prn><pes>/Eu<prn><tn><pes>/Meu<prn><tn><pes>/De mim<prn><tn><pes>$ ^kã’u<v><tv>/assustar<vblex>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$^,<cm>/,<cm>$” ^he<v><tv>/dizer<vblex>$ ^tóg<su>/ele<prn><tn>$^.<sent>/.<sent>$ “^Inh<prn><pes>/Eu<prn><tn><pes>/Meu<prn><tn><pes>/De mim<prn><tn><pes>$ ^mỹ<cir>/para<pr>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$ ^tóg<su>/ele<prn><tn>$ ^tỹ<cir>/por<pr>/com<pr>$^,<cm>/,<cm>$ ^ũ<prn>/alguém<prn><tn>$ ^nĩ<a>/no momento<adv>$ ^ven<v><tv><sg>/mostrar<vblex>$ ^nĩ<a>/no momento<adv>$ ^vẽ<a>/é<vblex>/era<vblex>/ser<vblex>$^,<cm>/,<cm>$ ^hã<o>/igual<adj>/parecido<adj>$ ^ra<cir>/para<pr>/apesar do<cnjadv>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$ ^tóg<su>/ele<prn><tn>$ ^tỹ<cir>/por<pr>/com<pr>$^,<cm>/,<cm>$ ^ã<prn>/teu<prn><tn>/seu<prn><tn>/você<prn><tn>/tu<prn><tn><p2><mf><sg>$ ^hã<o>/igual<adj>/parecido<adj>$ ^nĩ<a>/no momento<adv>$”^,<cm>/,<cm>$ ^he<v><tv>/dizer<vblex>$ ^tóg<su>/ele<prn><tn>$^.<sent>/.<sent>$^.<sent>/.<sent>
Chunker output:
apertium-transfer: Rule 1 .<sent>/.<sent>
apertium-transfer: Rule 2 mỹ<cir>/para<pr>
apertium-transfer: Rule 3 ã<prn>/tu<prn><tn><p2><mf><sg> tóg<su>/ele<prn><tn>
apertium-transfer: Rule 2 tỹ<cir>/por<pr>/com<pr>
apertium-transfer: Rule 2 ra<cir>/para<pr>/apesar do<cnjadv>
apertium-transfer: Rule 3 ã<prn>/tu<prn><tn><p2><mf><sg> tóg<su>/ele<prn><tn>
apertium-transfer: Rule 2 tỹ<cir>/por<pr>/com<pr>
apertium-transfer: Rule 1 .<sent>/.<sent>
apertium-transfer: Rule 1 .<sent>/.<sent>
“^default<default>{^Eu<prn><tn><pes>$}$ ^default<default>{^assustar<vblex>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$^default<default>{^,<cm>$}$” ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$ “^default<default>{^Eu<prn><tn><pes>$}$ ^pr<SP>{^para<pr>$}$ ^prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$}$ ^pr<SP>{^por<pr>$}$^default<default>{^,<cm>$}$ ^default<default>{^alguém<prn><tn>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^mostrar<vblex>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^é<vblex>$}$^default<default>{^,<cm>$}$ ^default<default>{^igual<adj>$}$ ^pr<SP>{^para<pr>$}$ ^prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$}$ ^pr<SP>{^por<pr>$}$^default<default>{^,<cm>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$ ^default<default>{^igual<adj>$}$ ^default<default>{^no momento<adv>$}$”^default<default>{^,<cm>$}$ ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$^sent<SENT>{^.<sent>$}$
Interchunk output:
apertium-interchunk: Rule 1 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$}
apertium-interchunk: Rule 2 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$} pr<SP>{^por<pr>$}
apertium-interchunk: Rule 1 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$}
apertium-interchunk: Rule 2 prn<SN><CD>{^tu<prn><tn><p2><mf><sg><2>$} pr<SP>{^por<pr>$}
“^default<default>{^Eu<prn><tn><pes>$}$ ^default<default>{^assustar<vblex>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$^default<default>{^,<cm>$}$” ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$ “^default<default>{^Eu<prn><tn><pes>$}$ ^pr<SP>{^para<pr>$}$ ^pr<SP>{^por<pr>$}$ ^prn<SN><obj>{^tu<prn><tn><p2><mf><sg><2>$}$^default<default>{^,<cm>$}$ ^default<default>{^alguém<prn><tn>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^mostrar<vblex>$}$ ^default<default>{^no momento<adv>$}$ ^default<default>{^é<vblex>$}$^default<default>{^,<cm>$}$ ^default<default>{^igual<adj>$}$ ^pr<SP>{^para<pr>$}$ ^pr<SP>{^por<pr>$}$ ^prn<SN><obj>{^tu<prn><tn><p2><mf><sg><2>$}$^default<default>{^,<cm>$}$ ^default<default>{^tu<prn><tn><p2><mf><sg>$}$ ^default<default>{^igual<adj>$}$ ^default<default>{^no momento<adv>$}$”^default<default>{^,<cm>$}$ ^default<default>{^dizer<vblex>$}$ ^default<default>{^ele<prn><tn>$}$^sent<SENT>{^.<sent>$}$^sent<SENT>{^.<sent>$}$
Postchunk output:
“^Eu<prn><tn><pes>$ ^assustar<vblex>$ ^tu<prn><tn><p2><mf><sg>$^,<cm>$” ^dizer<vblex>$ ^ele<prn><tn>$^.<sent>$ “^Eu<prn><tn><pes>$ ^para<pr>$ ^por<pr>$ ^tu<prn><tn><p2><mf><sg><obj>$^,<cm>$ ^alguém<prn><tn>$ ^no momento<adv>$ ^mostrar<vblex>$ ^no momento<adv>$ ^é<vblex>$^,<cm>$ ^igual<adj>$ ^para<pr>$ ^por<pr>$ ^tu<prn><tn><p2><mf><sg><obj>$^,<cm>$ ^tu<prn><tn><p2><mf><sg>$ ^igual<adj>$ ^no momento<adv>$”^,<cm>$ ^dizer<vblex>$ ^ele<prn><tn>$^.<sent>$^.<sent>$
kgp-por output:
“#Eu #assustar #tu,” #dizer #ele. “#Eu para por ti, #alguém #no momento #mostrar #no momento #é, #igual para por ti, #tu #igual #no momento”, #dizer #ele.
Post-evaluation
$ apertium-eval-translator -r ../tools/kgp.tests.txt -t ../ling073-kgp-por/kgp-por.tests.txt Test file: '../ling073-kgp-por/kgp-por.tests.txt' Reference file '../tools/kgp.tests.txt' Statistics about input files ------------------------------------------------------- Number of words in reference: 63 Number of words in test: 73 Number of unknown words (marked with a star) in test: Percentage of unknown words: 0.00 % Results when removing unknown-word marks (stars) ------------------------------------------------------- Edit distance: 72 Word error rate (WER): 114.29 % Number of position-independent correct words: 1 Position-independent word error rate (PER): 114.29 % Results when unknown-word marks (stars) are not removed ------------------------------------------------------- Edit distance: 72 Word Error Rate (WER): 114.29 % Number of position-independent correct words: 1 Position-independent word error rate (PER): 114.29 % Statistics about the translation of unknown words ------------------------------------------------------- Number of unknown words which were free rides: 0 Percentage of unknown words that were free rides: 0%
- WER: 114.29 % ???
- PER: 114.29 % ???
- Coverage:
$ aq-covtest ling073-kgp-por-corpus/kgp.tests.txt ling073-kgp-por/kgp-por.automorf.bin Number of tokenised words in the corpus: 80 Coverage: 100.00% Top unknown words in the corpus: Translation time: 0.002888202667236328 seconds
