Fix evaluate.py
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@ -29,7 +29,7 @@ correct = 0
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incorrect = 0
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for text, ground_act in zip(combined_df["value"].values, combined_df["act"].values):
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nla = NaturalLanguageAnalyzer()
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nla_output = nla.process(text)
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nla_output = nla.predict(text)
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predicted_act = set([i[0] for i in nla_output])
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pattern = re.compile(r'([^(&]+)(?=\()')
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