Linguistics

The urge to program human language originates for some in the quest for better explanation or understanding, for others in the improvement of communication. Both approaches have witnessed rapid evolution in recent years. Based on linguistics, psycholinguistics, sociolinguistics or neuroscientific advances, the potential of knowledge creation and communication has risen due to computational models and applications to linguistics. ChatGPT3 and Neuroflash allow us to play around with the commonly available AI-applications. Construction of a linguistically informed Glossary of political and social ideas is a specific application case. In addition to the subject/object list we may add predicates or verbs to link subjects and objects. For this purpose, we construct a basic alphabetical list below which draws mainly on action verbs and is embedded in the socio-cultural environment of the sciences in general. A categorised list of verbs, like the one from Purdue University, is helpful to draw on several relatively distinct fields. With perspective on labour market or societal relevance the list focuses on verbs related to skill sets: administrative/managerial; communication; creative, information/data; caring/helping; efficiency; research; teaching/learning; technical. The categories are not mutually exclusive and may well be supplemented by additional categories like relational skills and transformational skills. Computational psycholinguistics (Crocker, 2006 pdf-file) differentiate the “principle of incremental comprehension” (add one word at a time) from the “concentric theory of complexity” (start from complexity to specificity or vice-versa) and the “deductive sentence processor”. ChatGPT is built on the incremental approach, supposed to be the fastest and probably a more reliable computational approach. We could just attempt to use the other approaches in the simple ABC glossary of subjects, objects and predicates to test for the possibility to build no-nonsense short sentences using random choices as starting points. The Oxford handbook of psycholinguistics highlights in the final chapter the theoretical alternative of connectionism (p.811). Symbolic computation construes cognition as mental states that are symbolically represented. The sequence of operations then runs from one representation to the next one. However, the connectionist model operates more like a neural network and proceeds with the parallel processing of notions, relations or patterns. A list of predicates or verbs might do the trick: Chose a subject, chose a predicate and an object to start playing around: Subjects: action balance  corruption democracy enterprise freedom god health imagination joy knowledge law memory nature optimism policy question repairing society time union value war xeno yinyang zero.
Predicates: applies broadens creates directs establishes forms generates helps induces jeopardises  keeps likes moderates needs opposes prioritises qualifies represents strengthens tests uses varies weighs x-outs yields zigzags.
Objects:  freedom god health imagination joy knowledge law memory nature optimism policy question repairing society time union value war xeno yinyang zero action balance  corruption democracy enterprise.