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This application provides a different challenge, when compared to the previous examples, since it has very small input and output files (unlike N-Gram), but creates a large amount of intermediate data.
Understandably, this move is characterized by the future tense as indicated by the bolded auxiliary "will" across both examples, since it denotes events that will happen after the reference time of the writing.
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Teva is perhaps the best example, since it sells the blockbuster multiple sclerosis drug Copaxone.
This is a relatively safe example, since it's not a perennial issue around which partisan identities have been built.
It is easy to adjust the price of Sony, for example, since it is actively traded in New York as well as Tokyo.
The model is particularly well suited to information-rich goods, of which software is merely the most obvious example, since it is pure information.
a preference constraint is included only for the first and the second example (ie. the first should be ranked higher than the second), but not with the third example, since it has a different "qid".
It is also possible to get a particular nested relation into the FROM clause by use of the keyword THE, applied to a subquery whose result is a relation; the above query is an example, since it returns a whole nested relation.
We have chosen this example since it readily illustrates many ideas that will be developed in the following sections.
Predominant egoism is not troubled by the soldier counter-example, since it allows exceptions; it is not trivial; and it seems empirically plausible.
The Achilles is perhaps the best example since it employs only very ordinary notions, such as getting to where another has started from.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com