Developing a Word Sense Dataset Based on WordNet Hierarchy

• Main Authors: Cheng, Shang-Chien, 程尚謙
• Other Authors: Chang, Jason S.
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/3c68b4

碩士 === 國立清華大學 === 資訊系統與應用研究所 === 106 === We introduce a method for disambiguating word sense based on WordNet from a parallel corpus that can be used to provide accurate sense relevant translations and bilingual examples to support word sense disambiguation, as well as assist learning English with learner's native language (e.g., Chinese). In our approach, different translations of a word determine the specificity of the senses. The method involves extracting word translations, training a classifier to distinguish words into groups of senses based on translations, and selecting sense relevant example sentences. We present a prototype system, LanguageNet that applies the proposed method to display bilingual synonyms and sense relevant examples of senses of the given word. The evaluation on a set of polymous words shows that the method has good performance finding sense relevant translations and bilingual examples.