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facts-grounding-processed

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metadata
license: apache-2.0
tags:
  - factuality
  - grounding
  - llm-evaluation
  - text
  - preprocessing

Facts Grounding Processed

This dataset is a processed and reformatted version of google/FACTS-grounding-public, designed for LLM factuality and grounding evaluation.
It has been cleaned, enriched with additional metadata, and split into train and validation sets.

Dataset Summary

The dataset contains prompts, context documents, and target answers that challenge models to stay grounded in provided context rather than hallucinating.
Processing steps added extra features like:

  • prompt – consolidated instruction + user request + context
  • has_url_in_context – boolean flag for URLs in context
  • len_system, len_user, len_context – token/word length statistics
  • row_id – unique identifier for tracking

Dataset Structure

Splits:

  • train – 688 rows
  • validation – 172 rows

Features:

Feature Type Description
system_instruction string System-level instruction template
user_request string User query or prompt
context_document string Provided factual context
full_prompt string Original concatenated instruction + context
prompt string Processed consolidated prompt
has_url_in_context bool Whether the context contains a URL
len_system int64 Length of system instruction
len_user int64 Length of user request
len_context int64 Length of context document
target string Grounded factual answer
row_id int64 Unique row identifier

Processing

The preprocessing was done in Python with the Hugging Face datasets library:

  1. Loaded the original dataset (google/FACTS-grounding-public)
  2. Added custom features (URL detection, length counts)
  3. Generated combined prompt field
  4. Split into train (80%) and validation (20%)
  5. Exported as Arrow and JSONL formats

The preprocessing script is included in the repository for reproducibility.

Intended Uses

  • LLM grounding & hallucination evaluation
  • Prompt engineering experiments
  • Fine-tuning or zero/few-shot evaluation pipelines
  • Data formatting utilities

How to Use 

from datasets import load_dataset

dataset = load_dataset("GenAIDevTOProd/facts-grounding-processed")

print(dataset["train"][0])

License: 
This processed dataset is licensed under Apache 2.0.
The original data source is google/FACTS-grounding-public.