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Ontology learning (ontology extraction,ontology augmentation generation, ontology generation, or ontology acquisition) is the automatic or semi-automatic creation of ontologies, including extracting the corresponding domain's terms and the relationships between the concepts that these terms represent from a corpus of natural language text, and encoding them with an ontology language for easy ...
Wikicite is a free program that helps editors to create citations for their Wikipedia contributions using citation templates.It is written in Visual Basic .NET, making it suitable only for users with the .NET Framework installed on Windows, or, for other platforms, the Mono alternative framework.
WordNet is a lexical database of semantic relations between words that links words into semantic relations including synonyms, hyponyms, and meronyms. The synonyms are grouped into synsets with short definitions and usage examples. It can thus be seen as a combination and extension of a dictionary and thesaurus.
Flex (fast lexical analyzer generator) is a free and open-source software alternative to lex. [2] It is a computer program that generates lexical analyzers (also known as "scanners" or "lexers").
Finding duplicated references: a tool that will find references with the same URL on a page, with some false positives and missed items, is the URL Extractor For Web Pages and Text. It is not a Wikipedia tool, and there may be other tools available for the purpose. Instructions on its use for Wikipedia are in WP:DUPREF.
These text files can ultimately be any text format, such as code (for example C#), XML, HTML or XAML. T4 uses a custom template format which can contain .NET code and string literals in it, this is parsed by the T4 command line tool into .NET code, compiled and executed. The output of the executed code is the text file generated by the template ...
A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [ 3 ] providing relevant context, or describing a character for the AI to mimic.
The domain name for the thesaurus was registered on September 18, 2012. In 2015, the android and iOS app versions of the thesaurus were developed while its Chrome and Opera browser extensions were released in 2016. [5] [6]