Structural or syntactic ambiguity is the potential of multiple interpretations for a piece of written or spoken language because of the way words or phrases are organized. Linguistic ambiguity makes it difficult for a human or an AI system, such as a natural language processing (NLP) program, to determine meaning unless further information is available that clarifies the context.
Some structural ambiguity is the result of writing errors, such as misplaced modifiers. An example from Tom Sant’s book Persuasive Business Proposals: “Featuring plug-in circuit boards, we can strongly endorse this server’s flexibility and growth potential.”
That sentence might be intended to mean that the server has plug-in circuit boards, and a human would be likely to understand that. However, the way it’s organized, the sentence actually means that the writer features plug-in circuit boards, and software would be likely to require word sense disambiguation (WSD) to understand that is not the intended meaning.
The term structural ambiguity is often contrasted with lexical (word-related) ambiguity, which often arises because words can have multiple meanings. Both are examples of linguistic ambiguity, which also results from other things including figurative language and vagueness.