Cross-Lingual and Supervised Learning Approach for Indonesian Word Sense Disambiguation Task
Rahmad Mahendra, Heninggar Septiantri, Haryo Akbarianto Wibowo, Hendra Manurung, Mirna Adriani · 2018
Ambiguity is a problem we frequently face in Natural Language Processing.Word Sense Disambiguation (WSD) is a task to determine the correct sense of an ambiguous word.However, research in WSD for Indonesian is still rare to find.The availability of English-Indonesian parallel corpora and WordNet for both languages can be used as training data for WSD by applying Cross-Lingual WSD method.This training data is used as an input to build a model using supervised machine learning algorithms.Our research also examines the use of Word Embedding features to build the WSD model.