DrivelologyBinaryClassification

Overview

Drivelology Binary Classification evaluates models' ability to identify "drivelology" - a unique linguistic phenomenon characterized as "nonsense with depth." These are utterances that are syntactically coherent yet pragmatically paradoxical, emotionally loaded, or rhetorically subversive.

Task Description

Task Type: Binary Text Classification (Yes/No)
Input: Text sample to classify
Output: "Yes" if drivelology, "No" otherwise
Domain: Linguistic analysis, humor detection, pragmatics

Key Features

Tests understanding of layered linguistic meanings
Distinguishes nonsense-with-depth from pure nonsense and normal text
Requires contextual understanding and emotional insight
Covers humor, irony, sarcasm detection
Multiple difficulty levels available

Evaluation Notes

Default configuration uses 0-shot evaluation
Metrics: Accuracy, Precision, Recall, F1-Score
Subsets: binary-english-easy, binary-english-hard, binary-chinese-easy, binary-chinese-hard

Properties

Property	Value
Benchmark Name	`drivel_binary`
Dataset ID	extraordinarylab/drivel-hub
Paper	N/A
Tags	`Yes/No`
Metrics	`accuracy`, `precision`, `recall`, `f1_score`, `yes_ratio`
Default Shots	0-shot
Evaluation Split	`test`
Aggregation	`f1`

Data Statistics

Metric	Value
Total Samples	1,200
Prompt Length (Mean)	1056.08 chars
Prompt Length (Min/Max)	984 / 1449 chars

Sample Example

Subset: binary-classification

{
  "input": [
    {
      "id": "ddbda8da",
      "content": [
        {
          "text": "#Instruction#:\nClassify whether the given text is a Drivelology sample or not.\n\n#Definition#:\n- Drivelology: Statements that appear logically coherent but contain deeper, often paradoxical meanings.\nThese challenge conventional interpretation ... [TRUNCATED] ... ology.\n\n#Output Format#:\nYou should try your best to answer \"Yes\" if the given input text is Drivelology, otherwise specify \"No\".\nThe answer you give MUST be \"Yes\" or \"No\"\".\n\n#Input Text#: A: Name? B: Henry. A: Age? B: E-N-R-Y.\n#Your Answer#:"
        }
      ]
    }
  ],
  "target": "YES",
  "id": 0,
  "group_id": 0,
  "metadata": {
    "answer": "YES"
  }
}

Note: Some content was truncated for display.

Prompt Template

Prompt Template:

{question}

Few-shot Template

{question}

Usage

Using CLI

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets drivel_binary \
    --limit 10  # Remove this line for formal evaluation

Using Python

from evalscope import run_task
from evalscope.config import TaskConfig

task_cfg = TaskConfig(
    model='YOUR_MODEL',
    api_url='OPENAI_API_COMPAT_URL',
    api_key='EMPTY_TOKEN',
    datasets=['drivel_binary'],
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)

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