The Transition to Statistical Methods (1970s) › The Foundation: Formal Grammars and Linguistic Structure
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At the heart of symbolic language processing lies the concept of a grammar, a mathematical framework that specifies how words can legitimately combine to form sentences. Unlike the prescriptive grammar rules you might remember from school ("Don't split infinitives"), a formal grammar in language AI provides a generative system: a precise set of rules that can both recognize valid sentences and produce new ones.
Consider a simple grammar rule: Sentence → Noun Verb. This notation, borrowed from formal language theory, states that a sentence can be constructed by combining a noun with a verb. Applying this rule, we can generate "Birds sing" or "Cats sleep." We can extend this framework to handle more complex structures. For example, the rule Noun Phrase → Adjective Noun tells us that a noun phrase can consist of an adjective followed by a noun, allowing us to construct phrases like "blue sky" or "happy child." By chaining such rules together, we can describe increasingly sophisticated linguistic structures.
The theoretical foundation for this entire approach came from Noam Chomsky, whose work in the 1950s and 1960s revolutionized both linguistics and computer science. Chomsky proposed that beneath the surface diversity of human languages lay universal grammatical principles, shared structures that reflected fundamental properties of the human mind. His generative grammar aimed to capture these deep regularities through formal rules that could generate all and only the grammatical sentences of a language.
Chomsky's linguistic theories gave early AI a mathematical account of language structure. This made it seem plausible that computers could process language using the same kinds of rule-based algorithms they used for other symbolic tasks. The idea that language followed systematic patterns, expressible as computational procedures, gave researchers confidence that natural language understanding was achievable through symbolic manipulation.
Chomsky's rules could elegantly capture certain linguistic phenomena. The same grammatical framework that generates "The dog chased the cat" can also generate "The cat chased the dog," demonstrating how word order determines meaning. More sophisticated versions of transformational grammar could relate declarative sentences to their corresponding questions: transforming "The dog chased the cat" into "Did the dog chase the cat?" through explicit transformation rules. These capabilities made formal grammars powerful tools for analyzing linguistic structure, and they became the standard approach for the first several decades of language AI research.