Natural Language Processing (NLP), a vital subfield of computer science tied to artificial intelligence, empowers computers to understand and generate human language. Its origins date back to the 1950s, significantly influenced by Alan Turing's 1950 paper introducing the Turing test, which inherently involved automated language interpretation. The initial "Symbolic NLP" era, lasting until the early 1990s, relied on rule-based systems, leading to both ambitious but ultimately over-optimistic claims in early machine translation efforts like the 1954 Georgetown experiment. However, this period also saw remarkable creations such as Joseph Weizenbaum's ELIZA (1964-1966), a program that simulated a psychotherapist with startlingly human-like interactions. Despite setbacks, including a dramatic reduction in machine translation funding after the 1966 ALPAC report, research evolved through the 1970s and 80s with conceptual ontologies and early chatterbots, ultimately laying the groundwork for the more data-driven "statistical turn" in the 1990s.