Inductive Dependency Parsing

Cover -- Contents -- 1 Introduction -- 1.1 Inductive Dependency Parsing -- 1.2 The Need for Robust Disambiguation -- 1.3 Outline of the Book -- 2 Natural Language Parsing -- 2.1 Syntactic Representations -- 2.2 Two Notions of Parsing -- 2.2.1 Grammar Parsing -- 2.2.2 Text Parsing -- 2.2.3 Competence and Performance -- 2.3 Methods for Text Parsing -- 2.3.1 Grammar-Driven Text Parsing -- 2.3.2 Data-Driven Text Parsing -- 2.3.3 Converging Approaches -- 2.3.4 Inductive Dependency Parsing -- 2.4 Evaluation Criteria -- 2.4.1 Robustness -- 2.4.2 Disambiguation -- 2.4.3 Accuracy -- 2.4.4 Efficiency -- 3 Dependency Parsing -- 3.1 Dependency Grammar -- 3.1.1 The Notion of Dependency -- 3.1.2 Varieties of Dependency Grammar -- 3.2 Parsing with Dependency Representations -- 3.2.1 Grammar-Driven Dependency Parsing -- 3.2.2 Data-Driven Dependency Parsing -- 3.2.3 The Case for Dependency Parsing -- 3.3 A Framework for Dependency Parsing -- 3.3.1 Texts, Sentences and Tokens -- 3.3.2 Dependency Graphs -- 3.3.3 Dependency Parsing -- 3.4 Parsing Algorithm -- 3.4.1 Configurations -- 3.4.2 Transitions -- 3.4.3 Deterministic Parsing -- 3.4.4 Algorithm Analysis -- 3.4.5 Evaluation Criteria Revisited -- 4 Inductive Dependency Parsing -- 4.1 A Framework for Inductive Dependency Parsing -- 4.1.1 Data-Driven Text Parsing -- 4.1.2 Inductive Inference -- 4.1.3 History-Based Models -- 4.1.4 Parsing Methods -- 4.1.5 Learning Methods -- 4.1.6 Oracle Parsing -- 4.2 Features and Models -- 4.2.1 Feature Functions -- 4.2.2 Static Features -- 4.2.3 Dynamic Features -- 4.2.4 Feature Models -- 4.3 Memory-Based Learning -- 4.3.1 Memory-Based Learning and Classification -- 4.3.2 Learning Algorithm Parameters -- 4.3.3 Memory-Based Language Processing -- 4.4 Malt Parser -- 4.4.1 Architecture -- 4.4.2 Implementation -- 5 Treebank Parsing -- 5.1 Treebanks and Parsing -- 5.1.1 Treebank Evaluation -- 5.1.2 Treebank Learning -- 5.1.3 Treebanks for Dependency Parsing -- 5.2 Experimental Methodology -- 5.2.1 Treebank Data -- 5.2.2 Models and Algorithms -- 5.2.3 Evaluation -- 5.3 Feature Model Parameters -- 5.3.1 Part-of-Speech Context -- 5.3.2 Dependency Structure -- 5.3.3 Lexicalization -- 5.3.4 Efficiency -- 5.3.5 Learning Curves -- 5.4 Learning Algorithm Parameters -- 5.4.1 Neighbor Space and Distance Metric -- 5.4.2 Weighting Schemes -- 5.5 Final Evaluation -- 5.5.1 Accuracy and Efficiency -- 5.5.2 Related Work -- 5.5.3 Error Analysis -- 6 Conclusion -- 6.