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