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@@ -17,11 +17,17 @@ configs:
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  - split: train
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  path: data/train-*
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  license: apache-2.0
 
 
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  tags:
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- - croissant
 
 
 
 
 
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  ---
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-
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  ----------------------------------------------------------------
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  # Dataset Card for EnglishOCR Dataset
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  ### Curation Rationale
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  The EnglishOCR dataset was curated to support research and development on information extraction techniques and layout retain ability for unstructured documents in financial domain in English. By providing real-world company filings in unstructured format with ground truth, the dataset seeks to address challenges in extracting informat as well as layouts of complex documents, and convert into machine-readable format.
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- ### Source Data
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  #### Initial Data Collection and Normalization
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  - The source data are company filings from SEC EDGAR system.
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  - Subset of company filings in 2025 are downloaded in html format, and converted into correspondig pdf versions.
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  ### Dataset Curators
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  - Yueru He
 
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  ### Licensing Information
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- - **License:** CC BY 4.0
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  ### Citation Information
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- If you use this dataset in your research, please consider citing the following paper:
 
 
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  - split: train
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  path: data/train-*
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  license: apache-2.0
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+ language:
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+ - es
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  tags:
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+ - finance
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+ pretty_name: EnglishOCR
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+ size_categories:
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+ - 10K<n<100K
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+ task_categories:
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+ - image-to-text
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  ---
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  ----------------------------------------------------------------
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  # Dataset Card for EnglishOCR Dataset
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  ### Curation Rationale
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  The EnglishOCR dataset was curated to support research and development on information extraction techniques and layout retain ability for unstructured documents in financial domain in English. By providing real-world company filings in unstructured format with ground truth, the dataset seeks to address challenges in extracting informat as well as layouts of complex documents, and convert into machine-readable format.
 
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+ ### Source Data
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  #### Initial Data Collection and Normalization
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  - The source data are company filings from SEC EDGAR system.
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  - Subset of company filings in 2025 are downloaded in html format, and converted into correspondig pdf versions.
 
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  ### Dataset Curators
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  - Yueru He
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+ - The FinAI Team
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  ### Licensing Information
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+ - **License:** Apache License 2.0
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  ### Citation Information
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+ If you use this dataset, please cite:
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+
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+ ```bibtex
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