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  2. Named-entity recognition - Wikipedia

    en.wikipedia.org/wiki/Named-entity_recognition

    Named-entity recognition (NER) (also known as (named) entity identification, entity chunking, and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.

  3. Part-of-speech tagging - Wikipedia

    en.wikipedia.org/wiki/Part-of-speech_tagging

    A simplified form of this is commonly taught to school-age children, in the identification of words as nouns, verbs, adjectives, adverbs, etc. Once performed by hand, POS tagging is now done in the context of computational linguistics , using algorithms which associate discrete terms, as well as hidden parts of speech, by a set of descriptive tags.

  4. Naming convention (programming) - Wikipedia

    en.wikipedia.org/wiki/Naming_convention...

    Identifier type Rules for naming Examples Classes Class names should be nouns in UpperCamelCase, with the first letter of every word capitalised. Use whole words – avoid acronyms and abbreviations (unless the abbreviation is much more widely used than the long form, such as URL or HTML).

  5. CLAWS (linguistics) - Wikipedia

    en.wikipedia.org/wiki/CLAWS_(linguistics)

    A Part-Of-Speech Tagger (POS Tagger) is a piece of software that reads text in some language and assigns parts of speech to each word (and other token), such as noun, verb, adjective, etc., although generally computational applications use more fine-grained POS tags like 'noun-plural'. [2]

  6. Lexical analysis - Wikipedia

    en.wikipedia.org/wiki/Lexical_analysis

    In case of a natural language, those categories include nouns, verbs, adjectives, punctuations etc. In case of a programming language, the categories include identifiers, operators, grouping symbols and data types. Lexical tokenization is related to the type of tokenization used in large language models (LLMs) but with two differences.

  7. WordNet - Wikipedia

    en.wikipedia.org/wiki/WordNet

    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.

  8. Noun - Wikipedia

    en.wikipedia.org/wiki/Noun

    A proper noun (sometimes called a proper name, though the two terms normally have different meanings) is a noun that represents a unique entity (India, Pegasus, Jupiter, Confucius, Pequod) – as distinguished from common nouns (or appellative nouns), which describe a class of entities (country, animal, planet, person, ship). [11]

  9. Referring expression - Wikipedia

    en.wikipedia.org/wiki/Referring_expression

    a noun phrase of any structure, such as: the taxi in The taxi's waiting outside; the apple on the table in Bring me the apple on the table; and those five boys in Those five boys were off school last week. In those languages which, like English, encode definiteness, REs are typically marked for definiteness.

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