Humans proficiently interpret the true sense of an ambiguous word by establishing association among words in a sentence. The complete sense of text is also based on implicit information, which is not explicitly mentioned. The absence of this implicit information is a significant problem for a computer program that attempts to determine the correct sense of ambiguous words. In this paper, we propose a novel method to uncover the implicit information that links the words of a sentence. We reveal this implicit information using a graph, which is then used to disambiguate the ambiguous word. The experiments show that the proposed algorithm interprets the correct sense for both homonyms and polysemous words. Our proposed algorithm has performed better than the approaches presented in the SemEval-2013 task for word sense disambiguation and has shown an accuracy of 79.6 percent, which is 2.5 percent better than the best unsupervised approach in SemEval-2007.

中文翻译：

---

使用隐含信息的词义消歧

人类通过在句子中的单词之间建立关联来熟练地解释模棱两可的单词的真正含义。完整的文本意义也是基于隐含的信息，没有明确提及。对于试图确定歧义词的正确含义的计算机程序来说，这种隐含信息的缺失是一个重大问题。在本文中，我们提出了一种新的方法来发现链接句子单词的隐含信息。我们使用图表来揭示这些隐含信息，然后用它来消除歧义词。实验表明，所提出的算法解释了同音异义词和多义词的正确含义。