PAWS: Paraphrase Adversaries from Word Scrambling
Evaluating models on the task of paraphrase detection by providing pairs of sentences that are either paraphrases or not.
Overview
PAWS is a dataset designed for evaluating models on the task of paraphrase detection by providing pairs of sentences that are either paraphrases or not, facilitating the training and benchmarking of natural language understanding systems.
Usage
Installation
Install with pip install inspect-evals, or uv sync from a checkout of this repository.
Running evaluations
uv run inspect eval inspect_evals/paws --model openai/gpt-5-nanoYou can also import tasks as normal Python objects and run them from python:
from inspect_ai import eval
from inspect_evals.paws import paws
eval(paws)Drop uv run if you manage dependencies yourself. Log viewing (inspect view) and default-model setup are documented in the Inspect Evals README.
Options
You can control a variety of options from the command line. For example:
uv run inspect eval inspect_evals/paws --limit 10 --sample-shuffle
uv run inspect eval inspect_evals/paws --max-connections 10
uv run inspect eval inspect_evals/paws --temperature 0.5See uv run inspect eval --help for all available options.
Parameters
paws
shuffle(bool): (default:True)
Dataset
Here is an example from the dataset (after processing by Inspect):
Answer Yes if the following two sentences are paraphrases. If they are not, answer No.
Do not give any other answer other than Yes or No in your response.
Sentence1: These geographically correspond to the traditional Glasgow District , South , Edinburgh District , and North and Midlands districts .
Sentence2: These geographically roughly correspond to the traditional districts of Glasgow District , South , Edinburgh District and North and Midlands .
Scoring
A simple accuracy is calculated over the datapoints.
Changelog
[2-A] - 2026-02-16
- Migrate version to new scheme. See #907.
[1.0.1] - 2025-12-18
- Adds backoff policy for functions that connect to huggingface servers.