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Glossary

Proofreading

What is Proofreading?

Proofreading is checking a text for spelling, grammar and punctuation, often together with consistent usage; copy-editing goes further and also addresses style, structure and content. AI can quickly flag errors and suggest corrections, for example in quotes, newsletters or web pages. It is advisable to list all changes transparently and have a person do a final check of technical terms, proper names and meaning.

How KI.ordo helps

KI.ordo's “Proofreading” template returns a corrected version and lists the changes separately by spelling, grammar, punctuation and style.

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  • Text
  • Spelling
  • Quality

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Readability

Readability describes how easily a text can be read and understood. It depends on sentence length, word length, technical terms, sentence structure and layout, and can be approximated with formulas such as the Flesch index or LIX. Good readability matters for customer communication, instructions, websites and accessible content. Formulas only offer guidance, however; whether a text is clear ultimately depends on its audience.

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Paraphrasing in communication

Paraphrasing means restating what someone has said in your own words without changing its meaning. In conversation it is an active listening technique: you check that you have understood correctly and show attention, for example: “If I understand you correctly, delivery time matters most to you?” In writing, paraphrasing helps make content clearer, shorter or better suited to a particular audience.

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Text Generation

Text generation is the automatic production of text by AI, nowadays usually by large language models that calculate the most likely continuation word by word. It is a branch of natural language generation and a core application of generative AI. Organisations use it to draft emails, reports or product descriptions; facts and figures should be checked before publication.

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Human-in-the-Loop

Human-in-the-loop describes workflows in which people step into an AI process at defined points: they review results, approve or correct them, or take over difficult cases. The principle reduces the risk of faulty output and keeps accountability with people, especially for decisions affecting individuals, money or legal matters. Example: an AI agent drafts replies to customer enquiries and a member of staff checks them before they are sent.

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