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@@ -7,6 +7,22 @@ language:
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  pretty_name: Claim Stance
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  size_categories:
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  - 1K<n<10K
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for Claim Stance Dataset
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  ## Dataset Summary
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  This dataset contains 2,394 labeled Wikipedia claims for 55 topics. The dataset includes the stance (Pro/Con) of each claim towards the topic,
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  as well as fine-grained annotations, based on the semantic model of [Stance Classification of Context-Dependent Claims](https://aclanthology.org/E17-1024/) (topic target,
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  topic sentiment towards its target, claim target, claim sentiment towards its target, and the relation between the targets).
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  The dataset is divided into a training set (25 topics, 1,039 claims) and a test set (30 topics, 1,355 claims).
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  ## Dataset Structure
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  * topicId - internal topic ID
 
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  pretty_name: Claim Stance
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  size_categories:
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  - 1K<n<10K
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+ configs:
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+ - config_name: claim_stance
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+ data_files:
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+ - split: train
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+ path: "train.csv"
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+ - split: test
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+ path: "test.csv"
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+ - config_name: claim_stance_topic
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+ data_files:
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+ - split: train
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+ path: "train_topic.csv"
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+ - split: validation
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+ path: "dev_topic.csv"
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+ - split: test
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+ path: "test_topic.csv"
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+ ---
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  ---
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  # Dataset Card for Claim Stance Dataset
 
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  ## Dataset Summary
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+ ### Claim Stance
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+
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  This dataset contains 2,394 labeled Wikipedia claims for 55 topics. The dataset includes the stance (Pro/Con) of each claim towards the topic,
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  as well as fine-grained annotations, based on the semantic model of [Stance Classification of Context-Dependent Claims](https://aclanthology.org/E17-1024/) (topic target,
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  topic sentiment towards its target, claim target, claim sentiment towards its target, and the relation between the targets).
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  The dataset is divided into a training set (25 topics, 1,039 claims) and a test set (30 topics, 1,355 claims).
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+ ### Claim Stance Topic
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+
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+ This subset contains the claims (`text`) only associated with the `topic` in a different split to train-validation-test. Usage of this subset TBA.
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+
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  ## Dataset Structure
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  * topicId - internal topic ID