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CONCLUSIONS

A short review of applied linguistic systems has shown that only very simple tasks like hyphenation or simple spell checking can be solved on a modest linguistic basis. All the other systems should employ relatively deep linguistic knowledge: dictionaries, morphologic and syntactic analyzers, and in some cases deep semantic knowledge and reasoning. What is more, nearly all of the discussed tasks, even spell checking, have to employ very deep analysis to be solved with an accuracy approaching 100%. It was also shown that most of the language processing tasks could be considered as special cases of the general task of language understanding, one of the ultimate goals of computational linguistics and artificial intelligence.

 

IV. LANGUAGE AS A MEANING Û TEXT TRANSFORMER

IN THIS CHAPTER, we will return to linguistics, to make a review of several viewpoints on natural language, and to select one of them as the base for further studies. The components of the selected approach will be defined, i.e., text and meaning. Then some conceptual properties of the linguistic transformations will be described and an example of these transformations will be given.


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  1. CONCLUSIONS
  2. CONCLUSIONS
  3. CONCLUSIONS
  4. CONCLUSIONS
  5. Conclusions
  6. General Conclusions
  7. LOGICAL CONCLUSIONS.
  8. The composition exercises ask you to manipulate data. They also expect you to make inferences in order to come to conclusions about the data.




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RELATED SYSTEMS | POSSIBLE POINTS OF VIEW ON NATURAL LANGUAGE

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