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@@ -37,7 +37,7 @@ The EnglishOCR dataset contains images derived from regulatory documents from SE
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  ### Supported Tasks
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- - **Task:** Information Extraction
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  - **Evaluation Metrics:** ROUGE-1
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  ### Languages
@@ -83,12 +83,12 @@ The EnglishOCR dataset was curated to support research and development on inform
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  ### Personal and Sensitive Information
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- - The EnglishOCR dataset does not contain any personally identifiable information (PII) and is strictly focused on Greek text data for summarization purposes.
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  ## Considerations for Using the Data
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  ### Social Impact of Dataset
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- This dataset enables AI models to extract structured information from scanned financial documents in multiple languages, promoting transparency and accessibility. By aligning page-level PDF images with accurate ground truth text, it supports the development of fairer, more inclusive models that work across diverse formats and languages.
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  ### Discussion of Biases
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  - The source data is limited to company filings, it may underrepresent other financial document types such as tax records, bank statements, or private company reports, potentially limiting model generalizability.
 
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  ### Supported Tasks
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+ - **Task:** Image-to-Text
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  - **Evaluation Metrics:** ROUGE-1
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  ### Languages
 
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  ### Personal and Sensitive Information
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+ - The EnglishOCR dataset does not contain any personally identifiable information (PII) and is strictly focused on English-language regulatory data. No personal or sensitive information is present in the dataset.
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  ## Considerations for Using the Data
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  ### Social Impact of Dataset
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+ This dataset enables AI models to extract structured information from scanned financial documents, promoting transparency and accessibility. By aligning page-level PDF images with accurate ground truth text, it supports the development of fairer, more inclusive models that work across diverse formats and languages.
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  ### Discussion of Biases
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  - The source data is limited to company filings, it may underrepresent other financial document types such as tax records, bank statements, or private company reports, potentially limiting model generalizability.