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矛盾的,我亲爱的华生翻译的文本

矛盾的,我亲爱的华生翻译的文本

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NLP,Classification,Text Data Classification

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    README.md

    Content In this Getting Started Competition, we’re classifying pairs of sentences (consisting of a premise and a hypothesis) into three categories - entailment, contradiction, or neutral. Let’s take a look at an example of each of these cases for the following premise: He came, he opened the door and I remember looking back and seeing the expression on his face, and I could tell that he was disappointed. Hypothesis 1: Just by the look on his face when he came through the door I just knew that he was let down. We know that this is true based on the information in the premise. So, this pair is related by entailment. Hypothesis 2: He was trying not to make us feel guilty but we knew we had caused him trouble. This very well might be true, but we can’t conclude this based on the information in the premise. So, this relationship is neutral. Hypothesis 3: He was so excited and bursting with joy that he practically knocked the door off it's frame. We know this isn’t true, because it is the complete opposite of what the premise says. So, this pair is related by contradiction. This dataset contains premise-hypothesis pairs in fifteen different languages, including: **Arabic, Bulgarian, Chinese, German, Greek, English, Spanish, French, Hindi, Russian, Swahili, Thai, Turkish, Urdu, and Vietnamese.** Approach The dataset has multiple languages. Hence, I have translated Non-English sentences to English sentences using the Google Transcription python library. Acknowledgements The dataset is taken from https://www.kaggle.com/c/contradictory-my-dear-watson.
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