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The ICA for a given sentence is arrived at usually by way of constituency tests. Constituency tests (e.g. topicalization, clefting, pseudoclefting, pro-form substitution, answer ellipsis, passivization, omission, coordination, etc.) identify the constituents, large and small, of English sentences. Two illustrations of the manner in which ...
Example (a) suggests that Drunks and could put off the customers are constituents. Example (b) suggests that Drunks could and put off the customers are constituents. The combination of (a) and (b) suggest in addition that could is a constituent. Sentence (c) suggests that Drunks could put and off the customers are not constituents.
The prosentential theory of truth developed by Dorothy Grover, [4] Nuel Belnap, and Joseph Camp, and defended more recently by Robert Brandom, holds that sentences like "p" is true and It is true that p should not be understood as ascribing properties to the sentence "p", but as a pro-sentence whose content is the same as that of "p." Brandom ...
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In geology, a rock composed of different minerals may be a compositional data point in a sample of rocks; a rock of which 10% is the first mineral, 30% is the second, and the remaining 60% is the third would correspond to the triple [0.1, 0.3, 0.6]. A data set would contain one such triple for each rock in a sample of rocks.
Therefore, when David Kennedy, a pro-fessor in the anthropology department at John Jay College of Criminal Justice, in New York City, came to Cincinnati in the fall of 2006 to pitch a program he had devised to counter gang violence, the cops didn’t expect much. Kennedy was tall and slim, and in the dark clothes he favored there was something
The predicate calculus goes a step further than the propositional calculus to an "analysis of the inner structure of propositions" [4] It breaks a simple sentence down into two parts (i) its subject (the object (singular or plural) of discourse) and (ii) a predicate (a verb or possibly verb-clause that asserts a quality or attribute of the object(s)).
In this approach, constituent parsing is modelled like machine translation: the task is sequence-to-sequence conversion from the sentence to a constituency parse, in the original paper using a deep LSTM with an attention mechanism. The gold training trees have to be linearised for this kind of model, but the conversion does not lose any ...