|Semantic Engine, Natural Language & Semantics|
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Tropes performs different types of text analyses:
The statistics are used for various purposes, among others to create the graphs and set out the results.
The Frequent word categories and the Text Style are obtained by comparing the distribution of the occurrence frequency of the categories observed in the text with linguistic production norms. These norms have been derived from the study of a great number of different texts. They are stored in specific in-built tables.
The Equivalent Classes constitute groups of closely related meanings (common nouns, proper nouns, trademarks, etc.) appearing frequently throughout the text. For example, "father" and "mother" are grouped together into the "family" class.
The Reference Fields group together the words comprising the Equivalent Classes in order to enable the software to build up a representation of the context. To achieve this, the Semantic equivalents dictionary of Tropes is composed of three different classification levels. At the lowest level are the References, which are next merged more broadly into Reference fields 2, which, in turn, are merged into Reference fields 1.
In the example below, the word "Lord Chancellor" belongs to the "minister" Reference, included in the "government" field 2, which is part of the "politics" field 1. The "politics" field 1 includes broader concepts, such as "political system", "foreign policy", etc.
|Fields 1||Fields 2||References||Words|
|Politics||Government||Federal government||Federal government|
|Politics||Government||Head of Government||Head of Government|
|Politics||Government||Head of Government||Prime Minister|
|Politics||Government||Minister||Secretary of State|
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