How to beginner · 3 min read

How to post-edit machine translation

Quick answer

Post-edit machine translation by first generating a raw translation with a model like gpt-4o or claude-3-5-sonnet-20241022, then refining the output by prompting the model to improve fluency, fix errors, and adapt style. Use chat.completions.create with clear instructions to guide the post-editing process.

PREREQUISITES

Python 3.8+
OpenAI API key (free tier works)
pip install openai>=1.0

Setup

Install the openai Python package and set your API key as an environment variable for secure authentication.

bash

pip install openai>=1.0

output

Collecting openai
  Downloading openai-1.x.x-py3-none-any.whl (xx kB)
Installing collected packages: openai
Successfully installed openai-1.x.x

Step by step

This example shows how to generate a machine translation and then post-edit it by prompting the model to improve the translation quality.

python

import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

# Step 1: Generate raw machine translation
source_text = "Hello, how are you today?"
raw_translation_prompt = [
    {"role": "user", "content": f"Translate this to French: {source_text}"}
]
raw_response = client.chat.completions.create(
    model="gpt-4o",
    messages=raw_translation_prompt
)
raw_translation = raw_response.choices[0].message.content
print("Raw translation:", raw_translation)

# Step 2: Post-edit the translation
post_edit_prompt = [
    {"role": "user", "content": (
        f"Here is a machine translation: '{raw_translation}'. "
        "Please improve the translation for fluency, correctness, and natural style. "
        "Return only the improved translation."
    )}
]
post_edit_response = client.chat.completions.create(
    model="gpt-4o",
    messages=post_edit_prompt
)
post_edited_translation = post_edit_response.choices[0].message.content
print("Post-edited translation:", post_edited_translation)

output

Raw translation: Bonjour, comment êtes-vous aujourd'hui ?
Post-edited translation: Bonjour, comment allez-vous aujourd'hui ?

Common variations

Use claude-3-5-sonnet-20241022 for more nuanced post-editing with the Anthropic SDK.
Implement asynchronous calls with asyncio for higher throughput.
Stream the post-editing output for real-time feedback using stream=True in chat.completions.create.

python

import os
import asyncio
from openai import OpenAI

async def async_post_edit():
    client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

    raw_translation = "Bonjour, comment êtes-vous aujourd'hui ?"
    post_edit_prompt = [
        {"role": "user", "content": (
            f"Improve this translation for fluency and style: '{raw_translation}'. "
            "Return only the improved text."
        )}
    ]

    stream = await client.chat.completions.create(
        model="gpt-4o",
        messages=post_edit_prompt,
        stream=True
    )

    print("Streaming post-edited translation:", end=" ")
    async for chunk in stream:
        delta = chunk.choices[0].delta.content or ""
        print(delta, end="", flush=True)
    print()

asyncio.run(async_post_edit())

output

Streaming post-edited translation: Bonjour, comment allez-vous aujourd'hui ?

Troubleshooting

If the post-edited output is too verbose, add instructions like "Return only the translation without explanations."
If the model output is unchanged, increase the prompt clarity or use a stronger model like gpt-4o.
For API errors, verify your OPENAI_API_KEY environment variable is set correctly.

✅

Key Takeaways

Use a two-step approach: generate raw translation, then post-edit with clear instructions.
Leverage streaming and async calls for efficient post-editing workflows.
Choose models like gpt-4o or claude-3-5-sonnet-20241022 for best post-editing quality.

Verified 2026-04 · gpt-4o, claude-3-5-sonnet-20241022

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