形容詞的歧義辨析是個尚待解決的重要問題，找到辨析字義的有效方法，可以幫助自然語言處理中的其他研究，例如機器翻譯，更幫助電腦輔助語言學習上的閱讀困難。
在本論文中，我們提出新的演算法來幫助形容詞的歧義辨析。目前的歧義辨析系統限於名詞，因此著重在利用具歧義性目標字旁邊的所有關鍵字，而沒有考慮到這些關鍵字與目標字是否有句法上的關聯。我們提出一個辨析形容詞字義的方法，並利用句法訊息來擷取形容詞附近的相關字。本論文的做法，延伸Yarowsky (1995)的“one sense per collocation”概念，利用和相似的搭配字一起出現的字義通常都是一致的限制，採自舉法（bootstrapping），發展辨識形容詞字義的模型。做法上先在訓練階段，取得少量已標示字義之目標字形容詞的例句，擷取其各個字義之搭配字，再用這些已知字義與搭配字的資訊，來標示其他未標示之目標字形容詞。標示的方法是利用WordNet的上下位詞關係，計算搭配字和搭配字之間相似度。未標示字義的目標字形容詞就以其搭配字，找到最相似的一組已知字義和搭配字，來決定其字義。
經過實作，以廣泛使用的人工標示好之語料SemCor為基準，再加上SENSEVAL-2競賽所提供的語料，計算由這些語料擷取出的搭配字在WordNet上下位詞階級中的相關度之後，實驗結果得到一個88%準確率的訓練資料庫；此外以英國國家語料庫（British National Corpus）的資料測試，評估使用搭配字辨析形容詞字義的效率，經人工評估有接近92%的精確率。證明利用自舉法發展辨識形容詞字義的模型是相當有效的。

We present an approach for disambiguating word senses of an adjective in a given sentence based on collocates and semantic relationships in WordNet. In our approach, we use bootstrapping to learn a list of collocates for each word sense of the adjective from a small amount of sense-tagged samples and a very large untagged corpus.
The method involves extracting collocates, sense-labeled and unlabeled, of the adjective from the training data and untagged corpus, assigning labels to the unlabeled collocates by measuring WordNet-based similarities between labeled and unlabeled collocates, and building a WSD model from the labeled collocates. At runtime, collocates of the adjective are identified and compared with labeled collocates. The adjective is then disambiguate according to the sense labels of the three most similar collocates.
We experimented with an implementation of the proposed method using SemCor, Senseval-2 lexical sample training set, and British National Corpus (BNC). Evaluation on collocates of the six adjectives selected from Senseval-2 shows that the WordNet-based bootstrapping approach performs better than previous researches on word sense disambiguation (WSD) of adjectives. Therefore, it is reasonable to conclude that the accuracy of word sense disambiguation of adjectives can be improved by computing WordNet-based similarities among collocates of the adjectives.

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