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Merge is assumed to have certain formal properties constraining syntactic structure, and is implemented with specific mechanisms. In terms of a merge-base theory of language acquisition, complements and specifiers are simply notations for first-merge (read as "complement-of" [head-complement]), and later second-merge (read as "specifier-of ...
These have also been called sandwich words, [16] and classed among intercalative blends. [14] (When two words are combined in their entirety, the result is considered a compound word rather than a blend. For example, bagpipe is a compound, not a blend, of bag and pipe.)
In the version of Merge which generates a label, the label identifies the properties of the phrase. Merge will always occur between two syntactic objects: a head and a non-head. [9] For example, Merge can combine the two lexical items drink and water to generate drink water. In the Minimalist Program, the phrase is identified with a label.
Of these, only two are widely available ones on computers: one for hiragana, ゟ, which is a vertical writing ligature of the characters よ and り; and one for katakana, ヿ, which is a vertical writing ligature of the characters コ and ト. Lao uses three ligatures, all comprising the letter ຫ (h). As a tonal language, most consonant ...
Also apophthegm. A terse, pithy saying, akin to a proverb, maxim, or aphorism. aposiopesis A rhetorical device in which speech is broken off abruptly and the sentence is left unfinished. apostrophe A figure of speech in which a speaker breaks off from addressing the audience (e.g., in a play) and directs speech to a third party such as an opposing litigant or some other individual, sometimes ...
A Dictionary of Media and Communication describes hybrid genre as "the combination of two or more genres", which may combine elements of more than one genre and/or which may "cut across categories such as fact and fiction". [1] Hybrid genres are a longstanding element in the fictional process.
Mail merge consists of combining mail and letters and pre-addressed envelopes or mailing labels for mass mailings from a form letter. [1]This feature is usually employed in a word processing document which contains fixed text (which is the same in each output document) and variables (which act as placeholders that are replaced by text from the data source word to word).
These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words. Word2vec takes as its input a large corpus of text and produces a vector space , typically of several hundred dimensions , with each unique word in the corpus being assigned a corresponding vector in the space.