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  2. Natural language processing - Wikipedia

    en.wikipedia.org/wiki/Natural_language_processing

    Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence. It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval , knowledge representation and computational linguistics , a subfield of ...

  3. Textual entailment - Wikipedia

    en.wikipedia.org/wiki/Textual_entailment

    Textual entailment measures natural language understanding as it asks for a semantic interpretation of the text, and due to its generality remains an active area of research. Many approaches and refinements of approaches have been considered, such as word embedding , logical models, graphical models, rule systems, contextual focusing, and ...

  4. Natural-language programming - Wikipedia

    en.wikipedia.org/wiki/Natural-language_programming

    Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program .

  5. Language creation in artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Language_creation_in...

    When AI is used for translating between languages, it can even create a new shared language to make the process easier. Natural Language Processing (NLP) helps these systems understand and generate human-like language, making it possible for AI to interact and communicate more naturally with people.

  6. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  7. Semantic parsing - Wikipedia

    en.wikipedia.org/wiki/Semantic_parsing

    Though Semantic neural network and Neural Semantic Parsing [25] both deal with Natural Language Processing (NLP) and semantics, they are not same. The models and executable formalisms used in semantic parsing research have traditionally been strongly dependent on concepts from formal semantics in linguistics, like the λ-calculus produced by a ...

  8. Outline of natural language processing - Wikipedia

    en.wikipedia.org/wiki/Outline_of_natural...

    AlchemyAPI – service provider of a natural-language processing API. Google, Inc. – the Google search engine is an example of automatic summarization, utilizing keyphrase extraction. Calais (Reuters product) – provider of a natural-language processing services.

  9. Text corpus - Wikipedia

    en.wikipedia.org/wiki/Text_corpus

    Another example is indicating the lemma (base) form of each word. When the language of the corpus is not a working language of the researchers who use it, interlinear glossing is used to make the annotation bilingual. Some corpora have further structured levels of analysis applied. In particular, smaller corpora may be fully parsed.