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Ergativ (zkratka ERG, z lat. ergatīvus z řec. ἐργάτης = pracovník, činitel), zvaný též agenciál (z lat. agentiālis z agēns = činitel) je mluvnický pád, který v některých jazycích označuje podmět přechodného slovesa. V takových jazycích bývá jeho protějškem pád zvaný absolutiv, který označuje podmět nepřechodného slovesa a předmět přechodného slovesa.…
The analysis highlights Overview, Related Topics and Entities as prominent areas in the source structure around Ergativ.
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.
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See recurring relationship patterns around Ergativ before inspecting the individual extracted relationships.
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jazycích podmět absolutiv lat cāsus činitel zvaný pád označuje přechodného slovesa např ergativní předmět nominativu akuzativu severní austronéských indoevropských paštštině
TTTA extracted structured relationships around Ergativ. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
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The concept neighborhoods around Ergativ bring nearby vocabulary together. In this analysis, examples include Jazycích, Agenciál and Agentiālis. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Ergativ, one of the stronger structural bridges in this analysis connects Ergativ 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 Ergativ to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Overview, Related Topics & Entities, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Ergativ · CS edition · Analysis: TopicsToTalkAbout