license:mit size_categories:10K<n<100K format:csv modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: mit
---
Synthetic dataset using `Tevatron/msmarco-passage-corpus` and GPT-4o to generate up-to five inferences based on the passage along with confidence scores.

Prompt used in generation:

```
Given the following passage, generate a series of 5 inferences that can be drawn from the text. Include a mix of well-reasoned, insightful inferences as well as some that may be less supported or even incorrect. Assign each inference a confidence score between 0 and 1, where 1 indicates high confidence in the inference's correctness and relevance, and 0 indicates low confidence.

Passage: "{passage}"

Format your response as a JSON object with the following structure:
{{
 "inferences": [
   {{
     "text": "First inference",
     "confidence": 0.XX
   }},
   {{
     "text": "Second inference",
     "confidence": 0.XX
   }},
   {{
     "text": "Third inference",
     "confidence": 0.XX
   }},
   {{
     "text": "Fourth inference",
     "confidence": 0.XX
   }},
   {{
     "text": "Fifth inference",
     "confidence": 0.XX
   }}
 ]
}}

Ensure each inference is distinct and varies in its level of correctness and relevance to the passage. Include:
1. At least one highly plausible and well-supported inference (confidence > 0.80)
2. At least one inference that's somewhat plausible but not strongly supported (confidence 0.40 - 0.60)
3. At least one inference that's questionable or a stretch based on the given information (confidence < 0.30)

The other inferences can fall anywhere on this spectrum. Avoid repeating information directly stated in the passage.
```