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Automatic Extraction of Examples for Word Sense Disambiguation

Automatic Extraction of Examples for Word Sense Disambiguation

CONTENTS 5 4.3

CONTENTS 5 4.3 Senseval-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.4 Senseval-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.5 Senseval-3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.5.1 The All-Words Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.5.2 The Lexical Sample Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.5.3 Other Tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.6 Semeval-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 5 TiMBL: Tilburg Memory-Based Learner 44 5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 5.2 Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 6 Automatic Extraction of Examples for WSD 47 6.1 Overview of the System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 6.2 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6.2.1 Sense Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6.2.2 Source Corpora . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 6.2.3 Automatic Annotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 6.3 Data Preprocessing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 6.3.1 Basic Preprocessing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 6.3.2 Part-of-Speech Tagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 6.4 Training and Test Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 6.4.1 Feature Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 6.4.2 Training Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 6.4.3 Test Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 6.5 Algorithm Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 6.6 Parameter Optimizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 6.6.1 General Parameter Optimizations . . . . . . . . . . . . . . . . . . . . . . . . 60 6.6.2 Automatic Feature Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 6.7 Scoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 6.8 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 6.8.1 Supervised WSD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 6.8.2 Unsupervised WSD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 6.8.3 Semi-supervised WSD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

CONTENTS 6 6.8.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 6.9 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 7 Conclusion, Future and Related Work 74 7.1 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 7.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 7.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 References 77 A List of Abbreviations 89 B Pool of Features 90 C Training and Test Set (Senseval-3 English Lexical Sample Task) 92 D Graphs 93 E Tables 96

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