my brilliant solution

This commit is contained in:
Mikołaj Pokrywka 2023-03-29 10:54:51 +02:00
commit 331a2ba38c
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*~
*.swp
*.bak
*.pyc
*.o
.DS_Store
.token

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Challenging America word-gap prediction
===================================
Guess a word in a gap.
Evaluation metric
-----------------
LikelihoodHashed is the metric

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config.txt Normal file
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--metric PerplexityHashed --precision 2 --in-header in-header.tsv --out-header out-header.tsv

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FileId Year LeftContext RightContext
1 FileId Year LeftContext RightContext

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Word
1 Word

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import lzma
with lzma.open('dev-0/in.tsv.xz', 'r') as file:
for line in file:
line = line.decode("utf-8")
line = line.strip()
if 'I\t' in line:
print('am:0.9 :0.1')
elif 'you\t' in line:
print('are:0.9 :0.1')
elif 'he\t' in line:
print('is:0.9 :0.1')
elif 'she\t' in line:
print('is:0.9 :0.1')
else:
print('the:0.5 a:0.3 :0.2')

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