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Update README.md (#7)

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- Update README.md (94b52abc1f9f7af1cb292d90e2f4a671d41cb1c1)


Co-authored-by: Alessandra Pascale <AlessandraPascale@users.noreply.huggingface.co>

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- # Wikipedia Contradict Benchmark
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  <!-- Provide a quick summary 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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  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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  <!-- Provide a longer summary of what this dataset is. -->
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- Wikipedia Contradict Benchmark is a QA-based benchmark consisting of 253 human-annotated instances that cover different types of real-world knowledge conflicts.
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  Each instance consists of a question, a pair of contradictory passages extracted from Wikipedia, and two distinct answers, each derived from on the passages. The pair is annotated by a human annotator who identify where the conflicted information is and what type of conflict is observed. The annotator then produces a set of questions related to the passages with different answers reflecting the conflicting source of knowledge.
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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- Wikipedia Contradict Benchmark is given in JSON format to store the corresponding information, so researchers can easily use our data. There are 253 instances in total.
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  The description of each key (when the instance contains two questions) is as follows:
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  - **title:** Title of article.
 
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+ # Wikipedia contradict benchmark
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  <!-- Provide a quick summary 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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  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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  <!-- Provide a longer summary of what this dataset is. -->
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+ Wikipedia contradict benchmark is a QA-based benchmark consisting of 253 human-annotated instances that cover different types of real-world knowledge conflicts.
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  Each instance consists of a question, a pair of contradictory passages extracted from Wikipedia, and two distinct answers, each derived from on the passages. The pair is annotated by a human annotator who identify where the conflicted information is and what type of conflict is observed. The annotator then produces a set of questions related to the passages with different answers reflecting the conflicting source of knowledge.
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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+ Wikipedia contradict benchmark is given in JSON format to store the corresponding information, so researchers can easily use our data. There are 253 instances in total.
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  The description of each key (when the instance contains two questions) is as follows:
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  - **title:** Title of article.