8. A method for helping the understanding of a target language by generating and presenting one or more modified versions for at least one sample of said target language, said method being executed upon a computer, said method comprising the following steps: providing at least a closed extract stored in said computer, wherein said closed extract is a data set that contains references to the words of said sample, and optionally also references to additional words or localizers, wherein a localizer is a string of symbols, said string of symbols not being a word in said target language, providing at least two relations stored in said computer, wherein a relation is a data set that comprises the information required to perform one or more modifications upon said closed extract, activating at least one of said relations, wherein said activation applies to said closed extract the one or more modification that are associated to said one relation, said application producing a second closed extract, this second closed extract being a modified closed extract, filtering at least one of said closed extracts to create an open extract, said open extract being a text fragment in the target language optionally containing in addition one or more localizers, wherein an open extract that is produced after filtering a modified closed extract is one of said modified versions of said sample, presenting said open extract in said display, wherein at least one of said modified version differs from said sample in one of the ways included in the following plurality of ways: it contains additional words, or it contains some of the same words in different order, or it contains localizers, so that presenting said one or more modified version provides an aid to the user for understanding said sample.
8. A method for helping the understanding of a target language by generating and presenting one or more modified versions for at least one sample of said target language, said method being executed upon a computer, said method comprising the following steps: providing at least a closed extract stored in said computer, wherein said closed extract is a data set that contains references to the words of said sample, and optionally also references to additional words or localizers, wherein a localizer is a string of symbols, said string of symbols not being a word in said target language, providing at least two relations stored in said computer, wherein a relation is a data set that comprises the information required to perform one or more modifications upon said closed extract, activating at least one of said relations, wherein said activation applies to said closed extract the one or more modification that are associated to said one relation, said application producing a second closed extract, this second closed extract being a modified closed extract, filtering at least one of said closed extracts to create an open extract, said open extract being a text fragment in the target language optionally containing in addition one or more localizers, wherein an open extract that is produced after filtering a modified closed extract is one of said modified versions of said sample, presenting said open extract in said display, wherein at least one of said modified version differs from said sample in one of the ways included in the following plurality of ways: it contains additional words, or it contains some of the same words in different order, or it contains localizers, so that presenting said one or more modified version provides an aid to the user for understanding said sample. 9. A method as claimed in claim 8 , wherein at least one of said relations comprises more than one activation level, so that different modifications are applied to one of said closed extracts when said relation is activated to different activation levels.