Loading standard_eval_bpemb.py +4 −3 Original line number Diff line number Diff line Loading @@ -32,9 +32,10 @@ def get_word_embedding(word, model): # Create SemEval output # guideline: 62.6 (harmonic mean of person & spearman) -- my result: 56.270 (Pearson: 55.717, Spearman: 56.834) with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/test/subtask1-monolingual/output/de.test.bpemb_og.output-mean.txt", mode="w") as output: with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/test/subtask1-monolingual/data/de.test.data.txt", mode="r") as input: with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/\ test/subtask1-monolingual/output/de.test.bpemb_og.output-mean.txt", mode="w", encoding="utf-8") as output: with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/\ test/subtask1-monolingual/data/de.test.data.txt", mode="r", encoding="utf-8") as input: for line in input.readlines(): word1, word2 = line.split("\t") embd1 = get_word_embedding(word1, bpemb_de) Loading Loading
standard_eval_bpemb.py +4 −3 Original line number Diff line number Diff line Loading @@ -32,9 +32,10 @@ def get_word_embedding(word, model): # Create SemEval output # guideline: 62.6 (harmonic mean of person & spearman) -- my result: 56.270 (Pearson: 55.717, Spearman: 56.834) with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/test/subtask1-monolingual/output/de.test.bpemb_og.output-mean.txt", mode="w") as output: with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/test/subtask1-monolingual/data/de.test.data.txt", mode="r") as input: with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/\ test/subtask1-monolingual/output/de.test.bpemb_og.output-mean.txt", mode="w", encoding="utf-8") as output: with open("/home/aileen/heiBOX/BA/bias-mitigation-ba/semeval2017-task2/SemEval17-Task2/\ test/subtask1-monolingual/data/de.test.data.txt", mode="r", encoding="utf-8") as input: for line in input.readlines(): word1, word2 = line.split("\t") embd1 = get_word_embedding(word1, bpemb_de) Loading