Abstract
We propose a method of acquiring attribute words for a wide range of object classes from Japanese Web documents.The method is a simple unsupervised method that ranks candidate words according to the score that uses the statistics of lexicosyntactic patterns, HTML tags, and word occurrences, as clues.To evaluate the attribute words, we also establish an evaluation procedure based on the idea of question-answerability. Using the proposed evaluation procedure, we conducted experiments on 22 word classes with four human evaluators.The results revealed that our method can obtain attribute words with a high degree of precision and the clues used in the ranking actually contribute to the performance.
