mathiascreutz
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Minor modifications
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README.md
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`gem_id`: unique identifier of this entry
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### Data Splits
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The data is split into ...
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`gem_id`: unique identifier of this entry
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**Additional information about the annotation scheme:**
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The annotation scores given by an individual annotator are:
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4: Good example of paraphrases = Dark green button in the annotation
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tool = The two sentences can be used in the same situation and
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essentially "mean the same thing".
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3: Mostly good example of paraphrases = Light green button in the
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annotation tool = It is acceptable to think that the two sentences
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refer to the same thing, although one sentence might be more specific
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than the other one, or there are differences in style, such as polite
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form versus familiar form.
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2: Mostly bad example of paraphrases = Yellow button in the annotation
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tool = There is some connection between the sentences that explains
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why they occur together, but one would not really consider them to
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mean the same thing.
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1: Bad example of paraphrases = Red button in the annotation tool =
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There is no obvious connection. The sentences mean different things.
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If the two annotators fully agreed on the category, the value in the
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`annot_score` field is 4.0, 3.0, 2.0 or 1.0. If the two annotators
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chose adjacent categories, the value in this field will be 3.5, 2.5 or
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1.5. For instance, a value of 2.5 means that one annotator gave a
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score of 3 ("mostly good"), indicating a possible paraphrase pair,
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whereas the other annotator scored this as a 2 ("mostly bad"), that
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is, unlikely to be a paraphrase pair. If the annotators disagreed by
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more than one category, the sentence pair was discarded and won't show
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up in the datasets.
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The training sets were not annotated manually. This is indicated by
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the value 0.0 in the `annot_score` field.
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### Data Splits
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The data is split into ...
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