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Polysemy is a very common phenomenon in modern languages. Under manycircumstances, there exists a primal meaning for the expression. We define theprimal meaning of an expression to be a frequently used sense of thatexpression from which its other frequent senses can be deduced. Many of the newappearing meanings of the expressions are either originated from a primalmeaning, or are merely literal references to the original expression, e.g.,apple (fruit), Apple (Inc), and Apple (movie). When constructing a knowledgebase from on-line encyclopedia data, it would be more efficient to be aware ofthe information about the importance of the senses. In this paper, we wouldlike to explore a way to automatically recommend the primal meaning of anexpression based on the textual descriptions of the multiple senses of anexpression from on-line encyclopedia websites. We propose a hybrid model thatcaptures both the pattern of the description and the relationship betweendifferent descriptions with both weakly supervised and unsupervised models. Theexperiment results show that our method yields a good result with a P@1(precision) score of 83.3 per cent, and a MAP (mean average precision) of 90.5per cent, surpassing the UMFS-WE baseline by a big margin (P@1 is 61.1 per centand MAP is 76.3 per cent).

Primal Meaning Recommendation via On-line Encyclopedia