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| | license: apache-2.0 |
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| | # Semantic Integrity Analysis Dataset |
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| | ## Overview |
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| | This dataset is designed for detecting semantic integrity violations between sentence pairs. |
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| | Each data instance contains two sentences and a label indicating the semantic relationship between them. |
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| | The dataset supports multi-class text pair classification. |
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| | ## Task Description |
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| | Given two sentences (sentence1 and sentence2), the model must classify the relationship as: |
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| | - 0 → Contradiction |
| | - 1 → Inconsistency |
| | - 2 → Duplication |
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| | This task is similar to Natural Language Inference (NLI), but focuses on semantic validation within structured documents. |
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| | ## Dataset Structure |
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| | Each row contains: |
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| | - sentence1 (string) |
| | - sentence2 (string) |
| | - label (integer) |
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| | Example: |
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| | sentence1: "The report was submitted in 2022." |
| | sentence2: "The report was submitted in 2023." |
| | label: 1 |
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| | ## Label Description |
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| | | Label | Category | Meaning | |
| | |-------|-----------------|---------| |
| | | 0 | Contradiction | Opposite meaning between sentences | |
| | | 1 | Inconsistency | Conflicting details or mismatched facts | |
| | | 2 | Duplication | Same or nearly same meaning | |
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| | --- |
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| | ## Data Source |
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| | The dataset was created from four structured documents (doc1, doc2, doc3, doc4). |
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| | Sentence pairs were extracted and manually annotated. |
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| | ## Annotation Process |
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| | Annotation was performed manually based on semantic relationship guidelines. |
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| | Each sentence pair was reviewed and labeled into one of three categories. |
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| | ## Intended Use |
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| | This dataset can be used for: |
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| | - Fine-tuning transformer models |
| | - Semantic validation systems |
| | - Document integrity checking |
| | - NLP research on sentence-pair classification |
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| | --- |
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| | ## Limitations |
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| | - Limited dataset size |
| | - Domain-specific content may reduce generalization |
| | - Manual annotation may introduce bias |
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| | ## Ethical Considerations |
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| | The dataset does not contain sensitive personal information. |
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| | It is intended for research and educational use only. |
