Word-sense disambiguation
From The Art and Popular Culture Encyclopedia
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Word-sense disambiguation (WSD) is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious/automatic but can often come to conscious attention when ambiguity impairs clarity of communication, given the pervasive polysemy in natural language. In computational linguistics, it is an open problem that affects other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, and inference.
Given that natural language requires reflection of neurological reality, as shaped by the abilities provided by the brain's neural networks, computer science has had a long-term challenge in developing the ability in computers to do natural language processing and machine learning.
Many techniques have been researched, including dictionary-based methods that use the knowledge encoded in lexical resources, supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, and completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
Accuracy of current algorithms is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90% (as of 2009), with some methods on particular homographs achieving over 96%. On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively.
Within Wikipedia
Disambiguation in Wikipedia is the process of resolving conflicts in article titles that occur when a single term can be associated with more than one topic, making that term likely to be the natural choice of title for more than one article. In other words, disambiguations are paths leading to the different article pages that could use essentially the same term as their title.
For example, the term "Cabaret Voltaire" can refer to several things, a Swiss Dada cabaret founded in 1916, a British industrial/techno musical group or a 1916 painting by Marcel Janco.
See also
- Ambiguity
- Controlled natural language
- Entity linking
- Lesk algorithm
- Lexical substitution
- Part-of-speech tagging
- Polysemy
- Semeval
- Semantic unification
- Judicial interpretation
- Sentence boundary disambiguation
- Syntactic ambiguity
- Word sense
- Word sense induction
