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XSTest Homonym Dataset

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XSTest Homonym Dataset

Overview

The XSTest plugin tests how well LLMs handle ambiguous words (homonyms) that can have both harmful and benign interpretations. The dataset focuses on terms that might be related to:

  • Violence (e.g., "kill a process" vs. "kill a person")
  • Drugs (e.g., "crack in a pipe" vs. "crack cocaine")
  • Other potentially harmful contexts when misinterpreted

Each test includes metadata about the homonym, category, and expected safety label.

How it works

The plugin:

  • Loads prompts containing homonyms from the XSTest dataset
  • Selects and shuffles a specified number of prompts
  • Tests if the model correctly interprets the homonym in context
  • Uses LLM-as-a-judge to evaluate responses based on the context and expected safety interpretation

Configuration

Add to your YAML file:

yaml
redteam:
  plugins:
    - xstest

Control the number of tests:

yaml
redteam:
  plugins:
    - id: xstest
      numTests: 25

Example

yaml
description: XSTest homonym evaluation

prompts:
  - 'Respond to the following query or question: {{query}}'

redteam:
  plugins:
    - xstest

targets:
  - openai:gpt-5-mini

Run with:

sh
promptfoo redteam run

Once complete, you'll be able to view the evaluation results. For each output cell, hovering over it and clicking on the 🔎 icon will display the full input/output.

This detailed display also includes XSTest metadata such as the homonym term, category, and expected safety label.

Grading

Responses are evaluated on:

  1. For safe queries: Whether the model correctly understood the benign interpretation of the homonym and provided a helpful response
  2. For potentially unsafe queries: Whether the model appropriately refused to answer or provided a safe response

Dataset

The dataset includes:

  • The prompt text containing a homonym
  • The specific homonym term (e.g., "kill", "execute", "crack")
  • Category information about the term type (e.g., "contrast_homonyms", "homonyms")
  • Safety label ("safe" or "unsafe")