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@@ -31,6 +31,7 @@ configs:
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  - split: train
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  path: data/train-*
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  ---
 
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  Dataset for basic argumentation in online reviews
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@@ -38,7 +39,7 @@ The dataset aims to annotate online review sentences for basic argumentative qua
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  The label set descriptions are as follows. The respective RoBERTa models are linked as well.
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- Argument component: Distinguishes the argumentative component that is used. Can be one of: claim, premise, background.
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- Specificity: Differentiates between generic statements and more thoughtful user statements. Can be one of: general, specific, experience.
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- Sentiment: A positive, balanced, negative or neutral argumentative statement about the reviewed item.
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- Aspect: Provides more insight into what aspect of interest the argumentative statement covers. Can be one or more of: general sentiment, price, delivery, function and quality, fun and usage, style, installation, customer service and none. Only available for the Amazon review subset.
 
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  - split: train
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  path: data/train-*
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  ---
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+ # Dataset Card for "argureviews"
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  Dataset for basic argumentation in online reviews
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  The label set descriptions are as follows. The respective RoBERTa models are linked as well.
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+ - [Argument component](/nihiluis/argureviews-component-roberta_v1): Distinguishes the argumentative component that is used. Can be one of: claim, premise, background.
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+ - [Specificity](/nihiluis/argureviews-specificity-roberta_v1): Differentiates between generic statements and more thoughtful user statements. Can be one of: general, specific, experience.
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+ - [Sentiment](/nihiluis/argureviews-sentiment-roberta_v1): A positive, balanced, negative or neutral argumentative statement about the reviewed item.
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+ - [Aspect](/nihiluis/argureviews-aspect-roberta_v1): Provides more insight into what aspect of interest the argumentative statement covers. Can be one or more of: general sentiment, price, delivery, function and quality, fun and usage, style, installation, customer service and none. Only available for the Amazon review subset.