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Ali-Bhai/toolace-ragtruth-style-hallucinations

ToolACE RAGTruth-style Tool Hallucination Dataset This dataset was built from ToolACE tool-use dialogues and converted into a RAGTruth-style format for hallucination detection in tool calling. Task Given: query: user query context: tool response output: final assistant answer the goal is to classify whether the answer is grounded in the tool output or belongs to one of three hallucination types. Labels clean tool_output_conflict overgeneration… See the full description on the dataset page: https://huggingface.co/datasets/Ali-Bhai/toolace-ragtruth-style-hallucinations.

sourceHugging Faceotherupdated 4mo agoView on Hugging Face
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ToolACE RAGTruth-style Tool Hallucination Dataset

This dataset was built from ToolACE tool-use dialogues and converted into a RAGTruth-style format for hallucination detection in tool calling.

Task

Given:

  • query: user query
  • context: tool response
  • output: final assistant answer

the goal is to classify whether the answer is grounded in the tool output or belongs to one of three hallucination types.

Labels

  • clean
  • tool_output_conflict
  • overgeneration
  • missing_tool_action_recommendation

Synthetic hallucinated examples contain RAGTruth-style character-span labels in hallucination_labels.

Splits

The default files are the mixed clean + synthetic splits:

SplitFile
traintrain.jsonl
validationvalidation.jsonl
testtest.jsonl

Split label counts

json
{
  "train": {
    "overgeneration": 276,
    "clean": 834,
    "missing_tool_action_recommendation": 276,
    "tool_output_conflict": 276
  },
  "validation": {
    "clean": 103,
    "overgeneration": 37,
    "tool_output_conflict": 37,
    "missing_tool_action_recommendation": 37
  },
  "test": {
    "clean": 96,
    "missing_tool_action_recommendation": 37,
    "tool_output_conflict": 37,
    "overgeneration": 37
  }
}

Loading

python
from datasets import load_dataset

dataset = load_dataset("Ali-Bhai/toolace-ragtruth-style-hallucinations")
print(dataset)

If automatic split detection is not available in the runtime, use:

python
from datasets import load_dataset

dataset = load_dataset(
    "json",
    data_files={
        "train": "hf://datasets/Ali-Bhai/toolace-ragtruth-style-hallucinations/train.jsonl",
        "validation": "hf://datasets/Ali-Bhai/toolace-ragtruth-style-hallucinations/validation.jsonl",
        "test": "hf://datasets/Ali-Bhai/toolace-ragtruth-style-hallucinations/test.jsonl",
    },
)

Source and construction

The clean records were extracted from ToolACE dialogues with exact tool-call/tool-output matching. Synthetic hallucinations were injected using three controlled policies:

  1. 1.numeric/date tool-output conflict,
  2. 2.natural unsupported overgeneration,
  3. 3.recommendation of an unavailable tool.

See metadata/dataset_manifest.json for the full file manifest.