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Prompt engineering neboli prompt inženýrství (zkráceně promptování) je metodologie navrhování efektivních požadavků či dotazů (promptů) velkým jazykovým modelům (LLM). Jde o dílčí obor umělé inteligence a zpracování přirozeného jazyka. V prompt engineeringu jde o správnou formulaci úkolu, který má umělá inteligence (AI) provést, tak, aby výstup co…
The analysis highlights Historie, Techniky and Overview as prominent areas in the source structure around Prompt engineering.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Prompt engineering shows recurring relationship patterns in the source. For example, Prompt engineering → Obrázky, Wikimedia Commons Another extracted example is Prompt engineering → LLM, Prompt. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
prompt llm modelu promptu cot few-shot příkladů zero-shot engineering zpracování výstup více prompting uvažování chybí zdroj neboli inženýrství promptování promptů
TTTA extracted 6 structured relationships around Prompt engineering. Examples in this analysis include Prompt engineering → related to Externí odkazy → Obrázky and Prompt engineering → related to Externí odkazy → Wikimedia Commons. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Prompt engineering | related to Externí odkazy | Obrázky | 0.60 | section |
| Prompt engineering | related to Externí odkazy | Wikimedia Commons | 0.60 | section |
| Prompt engineering | related to Ladění prefixů | Prompt | 0.60 | section |
| Prompt engineering | related to Ladění prefixů | LLM | 0.60 | section |
| Prompt engineering | related to Reference | Prompt | 0.60 | section |
| Prompt engineering | related to Reference | Wikipedii | 0.60 | section |
The concept neighborhoods around Prompt engineering bring nearby vocabulary together. In this analysis, examples include Prompt, Modelu and Příkladů. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Prompt engineering, one of the stronger structural bridges in this analysis connects Prompt engineering with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Prompt engineering to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Historie, Techniky & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Prompt engineering · CS edition · Analysis: TopicsToTalkAbout