Skip to content

Latest commit

 

History

History

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
 
 
 
 
 
 
 
 
 
 

README.md

Baseline results

Word-level task

# Language precision recall f-measure lev. distance
1 English 20.99 28.79 24.28 2.69
2 Hungarian 20.88 27.81 23.85 3.54
3 Czech 22.10 19.72 20.84 2.94
4 Spanish 15.76 17.91 16.76 5.20
5 Russian 13.23 14.13 13.67 7.62
6 French 11.08 14.00 12.37 4.32
7 Italian 8.12 10.54 9.18 5.35
8 Latin 6.76 13.17 8.94 4.14

Categorical details by language

Russian - Multilingual BERT Tokenizer (cased)

category inflection derivation compound precision recall f_measure distance
000 no no no 6.77 16.10 9.53 1.38
001 no no yes 12.00 23.08 15.79 2.92
010 no yes no 14.39 21.71 17.31 4.62
011 no yes yes 14.74 18.25 16.31 7.12
100 yes no no 6.85 10.19 8.19 5.85
101 yes no yes 10.68 15.99 12.80 6.06
110 yes yes no 15.89 14.55 15.19 8.94
111 yes yes yes 7.70 7.63 7.66 9.61
all - - - 13.23 14.13 13.67 7.62

Italian - Multilingual BERT Tokenizer (cased)

category inflection derivation compound precision recall f_measure distance
000 no no no 2.70 6.97 3.89 1.59
001 no no yes 14.67 23.40 18.03 3.11
010 no yes no 14.11 19.16 16.25 3.77
011 no yes yes 10.53 13.95 12.00 5.79
100 yes no no 3.32 5.49 4.14 4.87
101 yes no yes 11.76 13.19 12.44 4.47
110 yes yes no 11.37 11.97 11.66 6.56
111 yes yes yes 11.11 10.64 10.87 7.09
all - - - 8.12 10.54 9.18 5.35

Hungarian - Multilingual BERT Tokenizer (cased)

category inflection derivation compound precision recall f_measure distance
000 no no no 2.61 7.36 3.85 1.83
001 no no yes 9.89 20.37 13.31 2.78
010 no yes no 22.96 31.70 26.63 2.84
011 no yes yes 19.01 25.56 21.80 3.60
100 yes no no 16.75 27.17 20.72 2.97
101 yes no yes 17.76 27.27 21.51 3.92
110 yes yes no 25.53 28.36 26.87 3.88
111 yes yes yes 23.93 27.89 25.76 4.66
all - - - 20.88 27.81 23.85 3.54

French - Multilingual BERT Tokenizer (cased)

category inflection derivation compound precision recall f_measure distance
000 no no no 6.55 16.23 9.33 1.48
001 no no yes 30.63 57.44 39.96 2.85
010 no yes no 12.60 18.44 14.97 3.81
011 no yes yes 16.31 22.22 18.81 5.45
100 yes no no 6.08 9.33 7.36 3.85
101 yes no yes 15.06 16.45 15.72 5.06
110 yes yes no 14.15 14.32 14.23 5.30
111 yes yes yes 6.67 5.68 6.13 8.37
all - - - 11.08 14.00 12.37 4.32

Spanish - Multilingual BERT Tokenizer (cased)

category inflection derivation compound precision recall f_measure distance
000 no no no 5.19 12.82 7.39 1.47
001 no no yes 9.89 15.52 12.08 2.76
010 no yes no 16.02 21.29 18.28 3.37
011 no yes yes 5.26 5.26 5.26 4.83
100 yes no no 11.52 15.79 13.32 4.62
101 yes no yes 10.57 11.82 11.16 5.59
110 yes yes no 20.21 19.29 19.74 6.11
111 yes yes yes 28.92 28.57 28.74 7
all - - - 15.76 17.91 16.76 5.2

English - BERT Tokenizer (uncased)

category inflection derivation compound precision recall f_measure distance
000 no no no 2.02 5.55 2.96 2.11
001 no no yes 46.60 64.11 53.97 1.42
010 no yes no 25.29 33.90 28.97 2.75
011 no yes yes 36.85 38.93 37.86 2.96
100 yes no no 12.16 19.14 14.87 2.73
101 yes no yes 51.57 50.12 50.83 1.51
110 yes yes no 24.92 26.17 25.53 3.31
111 yes yes yes 34.81 28.30 31.22 3.22
all - - - 20.99 28.79 24.28 2.69

Mongolian - BERT Tokenizer (uncased)

category inflection derivation compound precision recall f_measure distance
000 no no no 1.26 3.75 1.89 2.14
001 no no yes - - - -
010 no yes no 4.86 9.62 6.46 4.45
011 no yes yes - - - -
100 yes no no 6.22 12.52 8.31 3.50
101 yes no yes 0.00 0.00 0.00 5.33
110 yes yes no 6.45 10.18 7.90 5.94
111 yes yes yes - - - -
all - - - 5.89 10.59 7.57 4.51

Sentence-level task

Language Precison Recall F-measure Lev. distance
Czech 36.76 30.35 33.25 21.01
English 63.68 65.77 64.71 5.50
Mongolian 20.00 29.95 23.99 28.86