--- license: mit task_categories: - token-classification language: - he tags: - privacy - token-classification - security - text-masking - hebrew - pii-detection - ner pretty_name: GolemGuard size_categories: - 100K", "▁מ", "שתתף", ":", "▁דו", "לב", "▁שם", "▁טוב", "▁", "תאריך", "▁", "לידה", ":", "▁28.", "08.", "97", "▁כתובת", ":", "▁", "סחר", "וב", "▁דוד", "▁158", ",", "▁קרי", "ית", "▁", "ים", ",", "▁26", "76", "389", "▁אימייל", ":", "▁sa", "git", "ben", "dor", "760", "@", "live", ".", "com", "▁טלפון", ":", "▁+", "97", "2-", "58", "-28", "92", "208", "▁", "סיכום", "▁הפ", "גישה", ":", "▁בפ", "גישה", "▁זו", "▁", "נד", "ונה", "▁", "חשיבות", "▁", "שיפור", "▁התקשורת", "▁הפנימי", "ת", "▁בין", "▁הצוות", "ים", ".", "▁ה", "וח", "לט", "▁לבצע", "▁", "סדנאות", "▁ל", "הכשרה", "▁נוספת", "▁בשבוע", "▁הבא", ".", ""], "token_classes": ["O", "O", "O", "O", "B-FIRST_NAME", "I-FIRST_NAME", "B-LAST_NAME", "I-LAST_NAME", "O", "O", "O", "O", "O", "B-DATE", "I-DATE", "I-DATE", "O", "O", "B-STREET", "I-STREET", "I-STREET", "I-STREET", "I-STREET", "O", "B-CITY", "I-CITY", "I-CITY", "I-CITY", "O", "B-POSTAL_CODE", "I-POSTAL_CODE", "I-POSTAL_CODE", "O", "O", "B-EMAIL", "I-EMAIL", "I-EMAIL", "I-EMAIL", "I-EMAIL", "I-EMAIL", "I-EMAIL", "I-EMAIL", "I-EMAIL", "O", "O", "B-PHONE_NUM", "I-PHONE_NUM", "I-PHONE_NUM", "I-PHONE_NUM", "I-PHONE_NUM", "I-PHONE_NUM", "I-PHONE_NUM", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"], "input_ids": [0, 874, 177834, 12, 18133, 22849, 16804, 19767, 6, 174081, 6, 119583, 12, 12511, 17331, 14773, 86185, 12, 6, 214797, 18340, 67512, 78373, 4, 46050, 2754, 6, 448, 4, 1381, 11835, 119861, 194921, 12, 57, 15769, 776, 1846, 110216, 981, 24056, 5, 277, 167153, 12, 997, 14773, 18504, 10057, 48590, 12231, 154782, 6, 186708, 18338, 58366, 12, 65412, 58366, 8248, 6, 16747, 15703, 6, 148055, 6, 154997, 185983, 214547, 609, 7501, 192819, 448, 5, 364, 15662, 21295, 107543, 6, 199930, 657, 226909, 122485, 132299, 54641, 5, 2], "attention_mask": [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], "offset_mapping": [[0, 0], [0, 1], [1, 5], [5, 6], [7, 9], [9, 11], [12, 14], [15, 18], [19, 20], [19, 24], [25, 26], [25, 29], [29, 30], [31, 34], [34, 37], [37, 39], [40, 45], [45, 46], [47, 48], [47, 50], [50, 52], [53, 56], [57, 60], [60, 61], [62, 65], [65, 67], [68, 69], [68, 70], [70, 71], [72, 74], [74, 76], [76, 79], [80, 86], [86, 87], [88, 90], [90, 93], [93, 96], [96, 99], [99, 102], [102, 103], [103, 107], [107, 108], [108, 111], [112, 117], [117, 118], [119, 120], [120, 122], [122, 124], [124, 126], [126, 129], [129, 131], [131, 134], [136, 137], [136, 141], [142, 144], [144, 148], [148, 149], [150, 152], [152, 156], [157, 159], [160, 161], [160, 162], [162, 165], [166, 167], [166, 172], [173, 174], [173, 178], [179, 186], [187, 193], [193, 194], [195, 198], [199, 204], [204, 206], [206, 207], [208, 209], [209, 211], [211, 213], [214, 218], [219, 220], [219, 225], [226, 227], [227, 232], [233, 238], [239, 244], [245, 248], [248, 249], [0, 0]], "template_type": "meeting_summary"} ``` ## Considerations for Using the Data ### Social Impact of Dataset The dataset aims to improve privacy protection in Hebrew text processing by enabling better PII detection and masking. This has important applications in: | Application Area | Description | |-----------------|-------------| | Regulatory Compliance | Support for GDPR and PPLA requirements | | Document Processing | Privacy-preserving text analysis and storage | | Information Security | Automated PII detection and protection | | Data Loss Prevention | Real-time PII identification and masking | ### Discussion of Biases 1. Geographic Bias - Dataset focuses on Israeli context and formats 2. Name Distribution - While effort was made to include diverse names, distribution may not perfectly match population demographics ## Additional Information ### Dataset Curators Dataset was generated by [Liran Baba](https://huggingface.co/CordwainerSmith). ### Model Training Dataset was generated for training the [GolemPII-xlm-roberta-v1][model-link] model by Liran Baba (CordwainerSmith), model, demonstrating its effectiveness for PII detection and masking tasks in Hebrew text. [model-link]: https://huggingface.co/CordwainerSmith/GolemPII-xlm-roberta-v1 ### Recommended Uses | Use Case | Description | |----------|-------------| | Privacy Protection | Identifying and masking PII in Hebrew documents | | Compliance Checking | Automated PII detection for regulatory compliance | | Data Sanitization | Cleaning sensitive information from text data | | Information Security | Supporting data loss prevention systems | ### Quick Start ```python from datasets import load_dataset # Load dataset dataset = load_dataset("GolemGuard") # Example usage sample = dataset['train'][0] print(f"Original text: {sample['source_text']}") print(f"Masked text: {sample['masked_text']}") ``` ### Versioning This is the initial release of the dataset. Future versions may include: - Additional template types - Expanded entity coverage - Enhanced demographic representation - Additional language variants ## License The GolemGuard dataset is released under MIT License with the following additional terms: ``` MIT License Copyright (c) 2024 Liran Baba Permission is hereby granted, free of charge, to any person obtaining a copy of this dataset and associated documentation files (the "Dataset"), to deal in the Dataset without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Dataset, and to permit persons to whom the Dataset is furnished to do so, subject to the following conditions: 1. The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Dataset. 2. Any academic or professional work that uses this Dataset must include an appropriate citation as specified below. THE DATASET IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATASET OR THE USE OR OTHER DEALINGS IN THE DATASET. ``` ### How to Cite If you use this dataset in your research, project, or application, please include the following citation: For informal usage (e.g., blog posts, documentation): ``` GolemGuard Dataset by Liran Baba (https://huggingface.co/datasets/CordwainerSmith/GolemGuard) ``` For academic or professional publications: ``` Baba, L. (2024). GolemGuard: A Professional Hebrew PII Detection Dataset. Retrieved from https://huggingface.co/datasets/CordwainerSmith/GolemGuard Related model: GolemPII-xlm-roberta-v1 (https://huggingface.co/CordwainerSmith/GolemPII-xlm-roberta-v1) ``` ### Usage Examples When referencing in your code: ```python """ This code uses the GolemGuard dataset by Liran Baba (https://huggingface.co/datasets/CordwainerSmith/GolemGuard) """ from datasets import load_dataset dataset = load_dataset("GolemGuard") ``` When referencing in your model card: ```yaml dataset_info: - name: GolemGuard author: Liran Baba url: https://huggingface.co/datasets/CordwainerSmith/GolemGuard year: 2024 ```