Uambigu

Uambigu is a term used in linguistics, information retrieval, and natural language processing to denote the residual ambiguity that remains after applying standard disambiguation methods to text or data. Its name is a blend of un- and ambiguity, signaling that some sense distinctions persist despite analysis.

Uambigu describes the residual interpretive uncertainty that cannot be eliminated by conventional disambiguation methods because interpretations are equally supported by available evidence. It can involve lexical, syntactic, and semantic ambiguities that survive automated or manual disambiguation, reflecting limits in context, data quality, or model capability.

Measurement and usage: Researchers sometimes quantify uambigu with a score between 0 and 1 representing the fraction of items that maintain multiple high-scoring interpretations after disambiguation. A higher score signals greater persistent ambiguity, guiding dataset design, annotation protocols, and model evaluation.

Examples: In the sentence “I saw the man with the telescope,” two parses are plausible. If surrounding documents offer limited context, both interpretations may receive similar support, yielding a nonzero uambigu score. In large corpora with rich contextual cues, the uambigu score for such cases tends to be lower, though not necessarily zero.

See also: ambiguity, disambiguation, word sense disambiguation, syntactic ambiguity, coreference resolution, information retrieval.