CourseNatural Language Processing: The Complete Course · Module 9: Translation, Multilingual NLP and Evaluating Generation · part 62 of 73
Part 62 · Module 9: Translation, Multilingual NLP and Evaluating Generation

Lesson 3: Scoring translations and summaries, and their limits

58 min read·14 Oct 2026
Module 9 · Lesson 3 · About 55 minutes · Needs: basic Python; n-grams (Module 4 Lesson 1) and bootstrap intervals (Module 5 Lesson 2) help; this lesson loads its own models

The situation

It is Wednesday 4 November 2026, project week 9. German messages now arrive every day, and a translation model can turn them into English for Ines. Rosa asks one question: "How good is the English?" She asks the same about the thread summaries for her Monday report.

A translation can be right in many wordings and wrong by one word. This lesson scores 14 German translations and the Hartley thread summary four ways (simulated data).

14 GERMAN MESSAGES, HARD_TEST, SIMULATED German message HT42 and 13 more MarianMT opus-mt-de-en, CPU English output the hypothesis reference written by a person how good? exact match: 0 of 14
Each German message is translated by MarianMT (amber: a model's output) and compared with a human reference (green); none of the 14 matches its reference word for word, so exact match cannot score them.

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