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夏の集中勉強会/2012/注釈

夏の集中勉強会/2012

補足・注釈

全般

  • valid tree は grammar などの制約によって (特定の deductive system とは独立して) 定まる木
  • valid item は, 特定の deductive system によって導出できる item

という定義である. 同じ valid … という名前だけど全く異なる

  • valid tree を含む (さらに追加要件を満たす必要な場合もある) item は correct item (p.214 など)

Chapter 7

  • correct item の定義がない???

Chapter 8

  • p.214
    • (Lemma 8.1) valid tree → 定義は p.214
  • p.232 gap degree in al dependency tree と, gap degree in its binarisation が異なる例が, Fig.8.3 (p.242) にある.
    • p.241 (Sec. 8.5.4) には, 「元の依存木の gap degree <= binarisation の gap degree」との記述がある

Table of Contents 目次

1. Introduction 1-13 (13pp)

  • 1.1 Motivation ... 3
  • 1.2 Background ... 5
    • 1.2.1 Parsing natural language ... 5
    • 1.2.2 Robustness in grammar-driven parsers ... 7
    • 1.2.3 Parsing schemata ... 8
  • 1.3 Outline of the book ... 9
    • 1.3.1 Contributions ... 10
    • 1.3.2 Structure of the book ... 10

2. Preliminaries 15-34 (20pp)

  • 2.1 Context-free grammars ... 15
  • 2.2 Parsing algorithms and schemata ... 18
  • 2.3 The formalism of parsing schemata ... 25
    • 2.3.1 Deduction systems ... 25
    • 2.3.2 Parsing systems and parsing schemata ... 26
    • 2.3.3 Correctness of parsing schemata ... 30
    • 2.3.4 Relations between parsing schemata ...30
  • 2.4 Advantages of parsing schemata ... 32

3. A compiler for parsing schemata 37-61 (25pp)

  • 3.1 Motivation and goals ... 37
    • 3.1.1 Design goals ... 39
    • 3.1.2 Related work ... 40
  • 3.2 System architecture ... 41
  • 3.3 Generated code ... 42
  • 3.4 Reading schemata ... 44
  • 3.5 The code generation process ... 48
    • 3.5.1 Elementtypes ... 48
    • 3.5.2 Deduction step classes ... 50
    • 3.5.3 Deduction step code generation ... 51
    • 3.5.4 Search specifications ... 52
  • 3.6 Indexing ... 53
    • 3.6.1 Static analysis and index descriptors ...54
    • 3.6.2 Generation of indexing code ... 57
    • 3.6.3 Deduction step indexing ... 59
  • 3.7 Discussion ... 60

4. Practical complexity of constituency parsers 63-100 (38pp)

  • 4.1 Parsing natural language with CFGs ... 64
  • 4.2 Parsing with TAGs ... 70
    • 4.2.1 Tree-adjoining grammars ... 70
    • 4.2.2 Substitution and adjunction ... 73
    • 4.2.3 Properties of TAG ... 75
  • 4.3 Parsing schemata for TAG ... 76
  • 4.4 Parsing schemata for the XTAG English grammar ... 78
    • 4.4.1 Grammar conversion ... 79
    • 4.4.2 Feature structure unification ... 80
    • 4.4.3 Tree filtering ... 83
  • 4.5 Comparing several parsers for the XTAG grammar ...86
  • 4.6 Parsing with artificially-generated TAGs ... 89
  • 4.7 Overhead of TAG parsing over CFG parsing ...96
  • 4.8 Discussion ... 99

5. Error-repair parsing schemata 103-129 (27pp)

  • 5.1 Motivation ... 103
  • 5.2 Error repairin parsing schemata ... 104
  • 5.2.1 The formalism of error-repair parsing schemata ... 105
  • 5.2.2 A tree distance for edit distance-based repair ... 108
  • 5.3 Lyon’serror-repair parser ... 111
  • 5.3.1 Lyon is correct ... 113
  • 5.4 Obtaining minimal distance parses ... 121
  • 5.5 Global and regional error repair ... 124
  • 5.5.1 Performance of global and regional parsers ... 128
  • 5.6 Discussion ... 129

6. Transforming standard parsers into error-repair parsers 131-159 (29pp)

  • 6.1 From standard parsers to error-repair parsers ... 131
    • 6.1.1 Outline of the transformation ... 132
  • 6.2 Formal description of the error-repair transformation ... 135
    • 6.2.1 Some properties of trees and items ... 135
    • 6.2.2 Some properties of deduction steps ... 137
    • 6.2.3 The error-repair transformation ... 139
  • 6.3 Proof of correctness of the error-repair transformation ... 143
    • 6.3.1 Proof of Theorem 6.1 ... 145
    • 6.3.2 Proof of Theorem 6.2 ... 148
  • 6.4 Optimising the results of the transformation ...155
  • 6.5 Discussion ... 158

7. Dependency parsing schemata 163-205 (43pp)

  • 7.1 Motivation ... 163
  • 7.2 The formalism of dependency parsing schemata ... 165
  • 7.3 Parsing schemata for projective dependency parsers ...169
    • 7.3.1 Collins (1996) ... 169
    • 7.3.2 Eisner (1996) ... 171
    • 7.3.3 Eisner and Satta (1999) ... 172
    • 7.3.4 Yamada and Matsumoto (2003) ... 173
    • 7.3.5 Lombardo and Lesmo (1996) and other Earley-based parsers ... 174
    • 7.3.6 Nivre(2003) ... 176
    • 7.3.7 Covington’s projective parser (Covington, 2001) . 180
  • 7.4 Relations between dependency parsers ...180
    • 7.4.1 Yamada and Matsumoto (2003) → Eisner (1996) ... 181
    • 7.4.2 Eisner and Satta (1999) → Eisner (1996) ... 182
    • 7.4.3 Other relations ... 183
  • 7.5 Proving the correctness of dependency parsers ... 184
    • 7.5.1 Eisner and Satta (1999) is correct ... 184
    • 7.5.2 Yamada and Matsumoto (2003) is correct ... 185
    • 7.5.3 Eisner (1996) is correct ... 186
  • 7.6 Parsing schemata for non-projective dependency parsers ... 186
    • 7.6.1 Pseudo-projectivity ... 187
    • 7.6.2 Attardi (2006) and the MHk parser ... 187
    • 7.6.3 MST parser (McDonald et al., 2005b) ... 190
    • 7.6.4 Covington’s non-pro jective parser (Covington, 1990; 2001) ... 192
  • 7.7 Parsing schemata for Link Grammar parsers ...193
    • 7.7.1 Sleator and Temperley’s LG parser ... 196
    • 7.7.2 Adapting projective dependency parsers to LG ... 198
    • 7.7.3 Eisner (1996) for LG ... 200
    • 7.7.4 Eisner and Satta (1999) for LG ... 201
    • 7.7.5 Yamada and Matsumoto (2003) for LG ... 203
  • 7.8 Discussion ... 204

8. Mildly non-projective dependency parsing 207-244 (38pp)

  • 8.1 Motivation ... 207
  • 8.2 Preliminaries ... 209
  • 8.3 The WG1 parser ... 211
    • 8.3.1 WG1 parsing schema ... 211
    • 8.3.2 Proof of correctness for WG1 ... 214
    • 8.3.3 Computational complexity of WG1 ... 226
  • 8.4 The WGk parser ... 227
    • 8.4.1 WGk parsing schema ... 227
    • 8.4.2 Proof of correctness for WGk ... 229
    • 8.4.3 Computational complexity of WGk ... 230
  • 8.5 Parsing ill-nested structures ... 231
    • 8.5.1 TheMG1 and MGk parsers ... 231
    • 8.5.2 Complexity of MGk ... 234
    • 8.5.3 Proof of correctness for MGk ... 234
    • 8.5.4 Mildly ill-nested dependency structures ... 241
  • 8.6 Discussion ... 243

9. Conclusions 247-252 (6pp)

  • 9.1 Future work … 250

Questions 質問