Editing Graph theory (section)

=== Linguistics ===
Graph-theoretic methods, in various forms, have proven particularly useful in [[linguistics]], since natural language often lends itself well to discrete structure. Traditionally, [[syntax]] and compositional semantics follow tree-based structures, whose expressive power lies in the [[principle of compositionality]], modeled in a hierarchical graph. More contemporary approaches such as [[head-driven phrase structure grammar]] model the syntax of natural language using [[feature structure|typed feature structure]]s, which are [[directed acyclic graph]]s. 
Within [[lexical semantics]], especially as applied to computers, modeling word meaning is easier when a given word is understood in terms of related words; [[semantic network]]s are therefore important in [[computational linguistics]]. Still, other methods in phonology (e.g. [[optimality theory]], which uses [[lattice graph]]s) and morphology (e.g. finite-state morphology, using [[finite-state transducer]]s) are common in the analysis of language as a graph. Indeed, the usefulness of this area of mathematics to linguistics has borne organizations such as [http://www.textgraphs.org/ TextGraphs], as well as various 'Net' projects, such as [[WordNet]], [[VerbNet]], and others.