How-to-use Guide

A quick guide to engines, methodologies, and formality.

First and foremost, Lingonect^® is not a volume translation tool!

It is for words, phrases, sentences, and short paragraphs. Avoid excessive or consecutive copying and pasting of text, as this may cause the system to stop working.

NMTs vs. LLMs

When using Lingonect^®, it is important to understand the difference between NMTs (Neural Machine Translation) and LLMs (Large Language Models). While all engines support translation, more complex methodologies, such as localization, transcreation, culturalization, analysis, correction, and contextualization, are supported only by LLMs. Please note that if you select these methodologies for an NMT engine, you will not receive a response.

Consider each LLM as one single opinion. Every LLM has its own datasets and its own learning algorithm, so there isn't necessarily a single best one; it often depends on what you like most or understand best. Never trust only one LLM! For Western languages and cultures, models like ChatGPT, Claude, Gemini, or Mistral tend to shine; for Eastern European, something like Yandex or Alice may serve you better; and for Asian, Chinese in particular, Baidu, Alibaba, or Tencent. You are the human who decides what you need, what you like most, and what fits your purpose best. Lingonect^® recommends to always compare at least 3-4 different outputs.

NMTs always use bilingual corpora and are designed to translate by following the source text as closely as possible. While translation remains subjective, particularly in longer or more complex content pieces, translation allows for less creative interpretation than the other three methodologies.

Translation

Sticks as close as possible to the source. In some cases it has to select an entirely different expression or idiom, as it does not exist in the target, but otherwise it must be a direct reflection of the source text.

Localization

Localization involves adjusting translated content to fit specific formats, platforms, or media requirements. For example, when translating Google Ads copy from English to German, character limitations may require you to condense the text, as German often requires more space than English. Similarly, website localization may require adapting measurements, currencies, and formats to suit the target culture.

On Lingonect^®, the localization methodology provides a translation that is automatically adjusted to your desired length. Simply enter the maximum character count for your translation, and the tool will localize the text to fit those constraints.

After selecting localization with a character max limit, you can select translation, transcreation, or culturalization. Localization cannot be combined with analysis. If you select only localization, the system will automatically use translation as the primary methodology.

Transcreation

Transcreation captures the intent, style, and meaning of the source, then recreates it in the target. It is possible that the target text is quite different from the source, so that it best reflects the source intent.

Culturalization

Culturalisation starts from the target culture, not the source. It reimagines the text to fit the linguistic and cultural reality of the target market, drawing on its references, idioms, sensitivities, and conventions so the message belongs there rather than being adapted into it.

Analysis

Analysis does not translate. Instead it takes your source word, phrase, or sentence and explains its syntax, grammar, style, and meaning, written in the target language you have selected, so a learner can understand the source text. Because it produces an explanation rather than a translation, localization cannot be combined with analysis and the formality level has no effect.

Correction

Correction does not translate either. It proofreads your source-language input and fixes any objective grammar, syntax, spelling, punctuation, or style mistakes, returning the corrected text in the same language you wrote it in. Below a grey dotted line, it then gives a short, succinct explanation of what was corrected and why, written in the target language you have selected, just like the transliteration reading aid. Correction is an LLM-only methodology, so NMT engines will not return a result.

Unlike analysis, the formality level does apply to correction. If you leave it on Original, the corrected text keeps the formality of your input. If you pick a specific level, correction will not only fix the objective mistakes but also adjust the text to that register, for example correcting a casual note into polite, formal phrasing. Because the corrected text stays in your source language, honorific and humble become available based on your source language rather than the target.

Correction also has its own optional maximum character limit, just like localization. When you select correction, a Max characters box appears: enter a number and the corrected text will be rewritten to fit that limit; leave it blank for no limit.

Contextualization

Contextualization is a deep dive on a single word. Unlike the other methodologies, it accepts only one word at a time, written in your source language. In return you get a compact learner's entry, with all explanations written in the target language you have selected:

A concise definition and the nearest natural equivalent in the target language. If a word has more than one grammatical function — for example English need, which is both a noun and a verb — each function is defined separately so nothing is missed.
Important collocations and idioms that use the word.
Strong, relevant example sentences in the source language — each with an audio button to hear it spoken — alongside a backtranslation in the target language.
Synonyms — and, where a synonym is genuinely close, a note on how it subtly differs in nuance, register or use — plus the word's antonyms.
Full conjugations for any verb function and full declensions for any noun/adjective function the language inflects. A word that is both a noun and a verb shows both sets of tables.
Any other grammar points worth knowing that are specific to that word in the source language.

Key notes are colour-coded so the most important things stand out: green for must-know points, blue for key points, and red for important things to watch out for. Contextualization is an LLM-only methodology, and because it explains rather than translates, localization and the formality level do not apply.

Contextualization never relies on a single opinion. Every available LLM is asked for its own entry, and the best of all of them is then merged into the one entry you see — the correct forms, the widest set of genuinely useful collocations, idioms and examples, and the most natural target-language explanations, whichever model supplied them. This matters because no single model is best at every language: a model native to your target language usually writes the most natural explanations, while another may know the rarer forms or idioms. The LLMs that contributed are named underneath the entry, so you can always see where it came from. Because it asks every LLM, contextualization uses one request per LLM plus one for the merge, so it counts more against your daily request limit than a single translation, and takes longer to come back.

Selecting a methodology

When selected, the chosen methodology icon will turn bright green. If localization is selected and then another methodology is added, localization will turn a darker shade of green.

Formality levels

You can also select a formality level. Some formality levels are only relevant to certain languages:

Honorific and humble is only relevant to languages like Japanese, Korean, Thai, and Vietnamese. Original means that the target text reflects, as closely as possible, the source text's formality level. Ceremonial is reserved for very formal, official occasions. The rest of the formality levels should be self-explanatory.

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