A.2 Glossary of Specialized Terms 335 e Knowledge Base: A shorthand for the totality of knowledge possessed by an intelligent system during a certain interval of time (whether or not this knowledge is explicitly rep- resented). Put differently: this is an intelligence’s total memory contents (inclusive of all types of memory) during an interval of time. e Language Comprehension: The process of mapping natural language speech or text into a more “cognitive”, largely language-independent representation. In OpenCog this has been done by various pipelines consisting of dedicated natural language processing tools, e.g. a pipeline: text — Link Parser — RelEx > RelEx2Frame — Frame2Atom Atomspace; and alternatively a pipeline Link Parser > Link2Atom — Atomspace. It would also be possi- ble to do language comprehension purely via PLN and other generic OpenCog processes, without using specialized language processing tools. e Language Generation: The process of mapping (largely language-independent) cognitive content into speech or text. In OpenCog this has been done by various pipelines consisting of dedicated natural language processing tools, e.g. a pipeline: Atomspace + NLGen — text; or more recently Atomspace — Atom2Link — surface realization — text. It would also be possible to do language generation purely via PLN and other generic OpenCog processes, without using specialized language processing tools. e Language Processing: Processing of human language is decomposed, in CogPrime, into Language Comprehension, Language Generation, and Dialogue Control. e Learning: In general, the process of a system adapting based on experience, in a way that increases its intelligence (its ability to achieve its goals). The theory underlying CogPrime doesn’t distinguish learning from reasoning, associating, or other aspects of intelligence. e Learning Server: In some OpenCog configurations, this refers to a software server that performs “offline” learning tasks (e.g. using MOSES or