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A Jabberwocky sentence is a type of sentence of interest in neurolinguistics. Jabberwocky sentences take their name from the language of Lewis Carroll's well-known poem " Jabberwocky ". In the poem, Carroll uses correct English grammar and syntax, but many of the words are made up and merely suggest meaning.
Phrase structure rules break sentences down into their constituent parts. These constituents are often represented as tree structures (dendrograms). The tree for Chomsky's sentence can be rendered as follows: A constituent is any word or combination of words that is dominated by a single node. Thus each individual word is a constituent.
By contrast, generative theories generally provide performance-based explanations for the oddness of center embedding sentences like one in (2). According to such explanations, the grammar of English could in principle generate such sentences, but doing so in practice is so taxing on working memory that the sentence ends up being unparsable ...
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus.
Lexico-syntactic-based changes contain both lexical alterations and modifications in the sentence structure. An example might be transforming an active voice sentence like "The cat chased the mouse" into a passive voice "The mouse was chased by the cat," where both the sentence structure and some words are altered.
In transformational grammar, each sentence in a language has two levels of representation: a deep structure and a surface structure. [3] The deep structure represents a sentence's core semantic relations and is mapped onto the surface structure, which follows the sentence's phonological system very closely, via transformations.