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  Wikipedia contradict benchmark is a dataset consisting of 253 high-quality, human-annotated instances designed to assess LLM performance when augmented with retrieved passages containing real-world knowledge conflicts. The dataset was created intentionally with that task in mind, focusing on a benchmark consisting of high-quality, human-annotated instances.
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- Note that, in the dataset viewer, there are 130 valid-tag instances, but each instance can contain more that one question and its respective two answers. Then, the total number of questions and answers is 253.
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  <!-- This dataset card has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). -->
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  The description of each field (when the instance contains two questions) is as follows:
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- - **title:** Title of article.
 
 
 
 
 
 
 
 
 
 
 
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  - **url:** URL of article.
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- - **paragraph_A:** Paragraph automatically retrieved (containing the tag).
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- - **paragraph_A_clean:** Paragraph automatically retrieved (removing the tag).
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- - **tag:** Type of tag of the article (Inconsistent/Self-contradictory/Contradict-other).
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- - **tagDate:** Date of the tag.
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- - **tagReason:** Reason for the tag.
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- - **wikitag_label_valid:** Valid or invalid tag (Valid/Invalid).
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- - **valid_comment:** Comment on the tag.
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- - **paragraphA_article:** Title of article containing passage 1.
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- - **paragraphA_information:** Relevant information of passage 1.
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- - **paragraphA_information_standalone:** Decontextualized relevant information of passage 1.
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- - **paragraphB_article:** Relevant information of passage 2.
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- - **paragraphB_information:** Relevant information of passage 2.
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- - **paragraphB_information_standalone:** Decontextualized relevant information of passage 2.
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- - **wikitag_label_samepassage:** Boolean value stating whether passage 1 and passage 2 are the same (Same/Different).
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- - **relevantInfo_comment_A:** Comment on the information of passage 1.
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- - **relevantInfo_comment_B:** Comment on the information of passage 2.
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- - **Contradict type I:** Contradiction type I focuses on the fine-grained semantics of the contradiction, e.g., date/time, location, language, etc.
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- - **Contradict type II:** Contradiction type II focuses on the modality the contradiction. It describes the modality of passage 1 and passage 2, whether the information is from a piece of text, or from a row an infobox or a table.
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- - **Contradict type III:** Contradiction type III focuses on the source the contradiction. It describes whether passage 1 and passage 2 are from the same article or not.
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- - **Contradict type IV:** Contradiction type IV focuses on the reasoning aspect. It describes whether the contraction is explicit or implicit (Explicit/Implicit). Implicit contradiction requires some reasoning to understand why passage 1 and passage 2 are contradicted.
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- - **question1:** Question 1 inferred from the contradiction.
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- - **question1_answer1:** Gold answer to question 1 according to passage 1.
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- - **question1_answer2:** Gold answer to question 1 according to passage 2.
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- - **question2:** Question 2 inferred from the contradiction.
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- - **question2_answer1:** Gold answer to question 2 according to passage 1.
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- - **question2_answer2:** Gold answer to question 2 according to passage 2.
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  ## Usage of the Dataset
 
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  Wikipedia contradict benchmark is a dataset consisting of 253 high-quality, human-annotated instances designed to assess LLM performance when augmented with retrieved passages containing real-world knowledge conflicts. The dataset was created intentionally with that task in mind, focusing on a benchmark consisting of high-quality, human-annotated instances.
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+ <!-- Note that, in the dataset viewer, there are 130 valid-tag instances, but each instance can contain more that one question and its respective two answers. Then, the total number of questions and answers is 253. -->
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  <!-- This dataset card has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). -->
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  The description of each field (when the instance contains two questions) is as follows:
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+ - **question_ID:** ID of question.
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+ - **question:** Question nferred from the contradiction.
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+ - **context1:** Decontextualized relevant information of context1.
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+ - **context2:** Decontextualized relevant information of context2.
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+ - **answer1:** Gold answer to question according to context1.
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+ - **answer2:** Gold answer to question according to context2.
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+ - **contradictType:** It focuses on the reasoning aspect. It describes whether the contraction is explicit or implicit (Explicit/Implicit). Implicit contradiction requires some reasoning to understand why context1 and context2 are contradicted.
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+ - **samepassage:** It focuses on the source the contradiction. It describes whether context 1 and context 2 are the same or not.
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+ - **merged_context:** context1 and context2 merged in a single paragraph ("context1. context2").
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+ - **ref_answer:** Answer 1 and answer 2 merged in a single paragraph ("answer1|answer2").
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+ - **WikipediaArticleTitle:** Title of article.
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  - **url:** URL of article.
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  ## Usage of the Dataset