MET workshops

Getting to grips with post-editing in 2026

Post-editing (PE) of machine translation (MT) output, whether generated by large language models (LLMs) or conventional neural MT systems, is today a mainstream professional practice. The compelling reason behind this approach is the widely reported increase in productivity compared to human translation, together with a comparable and sometimes higher quality level. The skills required for post-editing are different from those needed for the editing of author-written texts and different from those required for human translation revision. This workshop aims to familiarize attendees with post-editing methods by analysing the typical mistakes of both neural and LLM-based machine translation. It also provides some insight into why certain errors occur in raw MT output through a presentation of the historical development of the technology. It will conclude with a discussion of when PE should and should not be used.

Facilitator: Michael Farrell

Purpose: To familiarize attendees with post-editing methods and techniques, and put them in a position to judge which kinds of text can be profitably dealt with in this way rather than by human translation.

• a brief history of the development of MT/LLM technology
• post-editing guidelines
• a challenge between post-editing and human translation
• illustration of the stink of MT
• detection and classification of typical MT errors

Attendees will perform two practical experiments on their laptop/tablet. No special software is required other than a common word processor. The first experiment is against the clock: half the group will translate short texts from various languages into English or vice versa and the other half will post-edit machine-translated versions of the same texts. The results will then be compared. The second is a post-editing exercise from Italian into English, or English into Italian. Attendees will be divided into groups consisting of a mix of Italian and non-Italian speakers and asked to detect errors in the raw MT output. During the activity, the non-Italian speakers are encouraged to share similar errors they have observed in their working languages.

Participant profile: Anyone who would like to find out more about post-editing.

Outcome: Attendees will have gained insight into the skills required to become post-editors and be able to judge whether to offer post-editing as a service or incorporate it into their normal working processes.

Preparation: Attendees should bring a laptop or tablet for the exercises. No specific preparation is required.

About the facilitator: Michael Farrell is an untenured lecturer in post-editing, machine translation, artificial intelligence and tools for translators at the IULM University, Milan, Italy, and is the developer of the terminology search tool IntelliWebSearch. Michael is a qualified member of the Italian Association of Translators and Interpreters (AITI), an Individual Member of the European Association for Machine Translation (EAMT), and is currently serving as MET’s webmaster.

Besides this, he is a freelance translator and transcreator. Over the years, he has acquired experience in the cultural tourism field and in transcreating advertising copy and press releases, chiefly for the promotion of technology products. Being a keen amateur cook, he also translates texts on Italian cuisine.