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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.
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.
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
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 |
Data Source
The dataset was created from four structured documents (doc1, doc2, doc3, doc4).
Sentence pairs were extracted and manually annotated.
Annotation Process
Annotation was performed manually based on semantic relationship guidelines.
Each sentence pair was reviewed and labeled into one of three categories.
Intended Use
This dataset can be used for:
- Fine-tuning transformer models
- Semantic validation systems
- Document integrity checking
- NLP research on sentence-pair classification
Limitations
- Limited dataset size
- Domain-specific content may reduce generalization
- Manual annotation may introduce bias
Ethical Considerations
The dataset does not contain sensitive personal information.
It is intended for research and educational use only.
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