Blog: Mens Latina — 2019–04–26
Having somewhat solved the problem of identifying Latin verb conjugations, today we return to the process of instantiating a silent pronoun to serve as the conceptual subject of an inflected Latin verb for which no subject is actually stated. We need to flesh out the flag-panel of the silent pronoun with the associative tags which will properly connect the unspoken subject to its associated verb. To do so we need to carve out LaParser as a Latin parsing module. Right now when we type in “tu amas qualia” the Mens Latina eventually outputs “EGO AMO QUALIA” because our input includes a personal pronoun as the subject of the verb. If we enter only “amas qualia”, the idea does not resurface as output because we have not yet coded the full instantiation of the silent subject.
When a verb is being instantiated with a stated subject, the parsing module uses the tsj time-of-subject variable to assign associative tags between the stated subject and the verb. So now we try using the tmg time-of-midgap variable to let the LaParser module attach a flag-panel not only to a tsj time-of-subject concept but also to a tmg time-of-midgap concept. In the diagnostic user mode, the two instantiations look exactly the same. When we type in “tu amas nil” for “You love nothing”, the AI eventually outputs “EGO AMO NIL”. Now we try entering “amas nil” to see if the Mens Latina can deal with the unstated subject of the verb. No, it did not work, because in the InStantiate() module we had commented out the formation of the silent concept.
We finally got the Latin AI to activate pronominal concepts for the input of a Latin verb without a stated subject by instantiating the silent pronoun with such values as the concept-number of the verb as a seq of the pronoun and with the tvb time-of-verb value as the tkb of the pronoun, but the algorithm is not yet perfect. We enter “audis nil” and the AI immediately responds “EGO AUDIO NIL” which shows that the AI is thinking with the self-concept of “EGO”. We enter “amas qualia” and the AI immediately answers “EGO AMO QUALIA”. Although some wrong verb-forms still creep in, they indicate a problem with the LaVerbGen() module. We have achieved the two basic goals of indentifying a Latin verb-conjugation and of activating a silent subject for the input of an inflected verb with no stated subject. Yesterday we also created the documentation webpage for the PraeScium() Latin mindboot module.