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Intuition was assessed by a sample of 11 Australian business leaders as a gut feeling based on experience, which they considered useful for making judgments about people, culture, and strategy. [45] Such an example likens intuition to "gut feelings", which — when viable [ clarification needed ] — illustrate preconscious activity.
The more familiar syntax approach analyzes phrases and sentences in terms of outward (surface) appearance, i.e. in terms of the words which they contain and how intuition groups them. Structural diagrams reflecting this method strive to depict constituent clusters in the word stream supplemented by labels, perhaps, or other information of focal ...
The sentence appears on a computer monitor word-by-word. After each word, participants were asked to choose if the sentence is still grammatical so far. Then they would go on to rate the sentence from 1 "perfectly good English" to 7 "really bad English." The result showed that ungrammatical sentences were rated to be better than the grammatical ...
Perhaps the ultimate document structuring challenge is to generate a good narrative—in other words, a text which starts by setting the scene and giving an introduction/overview; then describes a set of events in a clear fashion, so readers can easily see how the individual events are related and link together; and concludes with a summary/ending.
For example, in many variants of transformational grammar, the English active voice sentence "Emma saw Daisy" and its passive counterpart "Daisy was seen by Emma" share a common deep structure generated by phrase structure rules, differing only in that the latter's structure is modified by a passivization transformation rule.
Tacit knowledge or implicit knowledge is knowledge that is difficult to extract or articulate—as opposed to conceptualized, formalized, codified, or explicit knowledge—is more difficult to convey to others through verbalization or writing. Examples of this include individual wisdom, experience, insight, motor skill, and intuition. [1]
[14] When sentences are directly generated by the system of grammatical rules, they are called "perfectly" or "strictly well-formed" grammatical sentences. [15] When sentences are "derivatively generated" by "relaxing" some grammatical rules (such as "subcategorization rules" or "selectional rules" [15]), they deviate from strictly well ...
Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence. Word2vec was developed by Tomáš Mikolov and colleagues at Google and published in 2013. Word2vec represents a word as a high-dimension vector of numbers which capture relationships between words.
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