This paper proposes a method for Named Entity (NE) extraction using NE-related labels of words repeatedly collected from unlabeled data. NE-related labels of words are candidate NE classes of each word, NE classes of co-occurring words of each word, and so on. To collect NE-related labels of words, we extract NEs from unlabeled data with an NE extractor. Then we collect NE-related labels of words from the extraction results. We create a new NE extractor using the NE-related labels of each word as new features. The new NE extractor is used to collect new NE-related labels of words. The experimental results using IREX data set for Japanese NE extraction show that our method contributes improved accuracy.