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Named Entity Recognition (NER) and Word Sense Disambiguation (WSD) is two of the major tasks of NLP. NER is the classification and extraction process of word(s) considered significant in a text. This significant word(s) can differ according to field. For example, this entities may be percentages, dates as well as person names, location names and company names, etc. WSD is an open problem in NLP. It consists of identifying the sense of a word, when having multiple meaning, in a sentence. WSD tries to identify litteral expressions of a word, not figurative expressions. Figurative Language Processing is the study similar and all but subfield of WSD. Figurative Language Processing concentrates on determining figurative expressions except litteral expressions.