add readme

README.md

@@ -0,0 +1,10 @@
+# Transfix-mt
+
+Part of the Transfix project responsible for injecting the dictionary into
+source data for constrained translation.
+The scripts are compatible with a gonito challenge that will be linked here in the future.
+
+It should used in the following way in a Transfix-like environment/file structure:
+* git clone https://git.wmi.amu.edu.pl/s470607/transfix-mt.git
+* ./transfix-mt/env/venv-setup.sh
+* ./transfix-mt/do_inject.sh

scripts/inject.py

@@ -41,11 +41,8 @@ def get_injected(sentence, sentence_en, sequence, inject):
 
 THRESHOLD = 70
 
-# train_in_path = '~/mt-summit-corpora/train/in.tsv'
+train_in_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/in.tsv')
-# train_expected_path = '~/mt-summit-corpora/train/expected.tsv'
+train_expected_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/expected.tsv')
-
-train_in_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/dev-0/in.tsv')
-train_expected_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/dev-0/expected.tsv')
 
 glossary = pd.read_csv('~/mt-summit-corpora/glossary.tsv.lemmatized', sep='\t')
 glossary['source_lem'] = [str(default_process(x)) for x in glossary['source_lem']]

scripts/lemmatize_glossary.py

@@ -1,4 +1,5 @@
 import nltk
+import os
 import pandas as pd
 
 from nltk.stem import WordNetLemmatizer
@@ -7,7 +8,7 @@ nltk.download('wordnet')
 
 wl = WordNetLemmatizer()
 
-glossary_path = '~/mt-summit-corpora/glossary.tsv'
+glossary_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/glossary.tsv')
 
 glossary = pd.read_csv(glossary_path, sep='\t', header=None, names=['source', 'result'])
 source_lemmatized = []

scripts/lemmatize_in.py

@@ -6,11 +6,8 @@ from nltk.stem import WordNetLemmatizer
 
 wl = WordNetLemmatizer()
 
-# train_in_path = '~/mt-summit-corpora/train/in.tsv'
+train_in_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/in.tsv')
-# train_expected_path = '~/mt-summit-corpora/train/expected.tsv'
+train_expected_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/train/expected.tsv')
-
-train_in_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/dev-0/in.tsv')
-train_expected_path = os.path.join(os.path.expanduser('~'), 'mt-summit-corpora/dev-0/expected.tsv')
 
 file_lemmatized = []
 with open(train_in_path, 'r') as file:
@@ -19,6 +16,7 @@ with open(train_in_path, 'r') as file:
             print('lemmatizing file: ' + train_in_path + ': ' + str(len(file_lemmatized)), end='\r')
         line = nltk.word_tokenize(line)
         file_lemmatized.append(' '.join([wl.lemmatize(x) for x in line]))
+print('\n')
 
 with open(train_in_path + '.lemmatized', 'w') as file_write:
     for line in file_lemmatized: