Victor Sadler

WORKING

WITH

ANALOGICAL SEMANTICS:

Disambiguation Techniques in DLT

 

 1989

FORIS PUBLICATIONS

Dordrecht – Holland/Providence RI – U.S.A.

 

(Distributed Language Translation 5)

 

[copyright Mouton de Gruyter]

 

Table of Contents

Acknowledgements … 8
Introduction   9

Part I: Prototype R&D

Chapter 1.  The field: Types of ambiguity relevant to machine translation   15

1.1   Types and terms …. 17

1.1.1           Lexical ambiguity … 18

1.1.2           Relational ambiguity … 19

1.2   The scale of difficulty … 25

Chapter 2.  The background: Development of the prototype architecture … 27

2.1          Dumb syntax, smart semantics … 30

2.2    The knowledge sources … 33

 

2.2.1            Potential sources … 33

2.2.2    Knowledge sources in the prototype … 36

Chapter 3. The theory: Assessing plausibility … 39

3.1          What constitutes plausibility? … 40

3.2    Methods of assessing plausibility … 41

 

3.2.1            The conventional approach: features and primitives … 41

3.2.2    The DLT prototype: collecting the evidence … 43

3.2.3            The first DLT prototype: making meaning explicit … 46

3.2.4    The second DLT prototype: leaving meaning implicit … 50

Chapter 4.  The techniques: Reasoning by analogy … 53

4.1           The word match … 55

4.2    Disambiguating the source language … 59

 

4.2.1            Lexical choice: the word pair match … 59

4.2.2    The Y match … 61

4.2.3    The X match  … 62

4.2.4    Combining the X and Y matches … 64

4.2.5    Combining word pair matches … 64

4.2.6    Resolving relational ambiguities … 66

4.2.7    The disambiguation dialogue … 68

4.3  Disambiguating the intermediate language … 71

4.3.1    Contextual cues in the bilingual dictionary … 72

4.3.2    Word match and expectancy match … 74

4.3.3    Method of the expectancy match … 76

4.3.4    Combining the match scores    77

4.3.5    Functional disambiguation …  78

Chapter 5.  The evaluation: Tests and limitations   81

5.1   Some tests of SWESIL   82

5.1.1            Testing the word match function …  82

5.1.2    Testing the word pair match function … 86

5.1.3    The Meijby Test … 89

5.1.4    Applications for referential disambiguation   98

5.2   The limitations of SWESIL   99

5.2.1            Strategic problems …  99

5.2.2    Limitations on existing functions … 102

5.2.3    Adding new functions … 104

Part II: Design for a production system

Chapter 6.   The Bilingual Knowledge Bank:  An integrated knowledge source for machine translation … 109

6.1    Rationale for a BKB … 110

6.1.1            Objectivity: the corpus as primary knowledge resource    110

6.1.2    Dictionary building: the need for a bilingual corpus    111

6.1.3    Reversibility: the use of bilingual context …   112

6.1.4    Consistency: discarding the LKB …   114

6.1.5    Quantity: structuring the corpus …   116

6.1.6    Scope: increasing the breadth of knowledge    119

6.1.7    Specificity: processing encyclopaedic knowledge …   122

6.1.8    Sensitivity: distinguishing word senses …   124

6.1.9    Productivity: towards full alignment …   126

 

6.1.10    Dynamicity: updating the knowledge sources …   131

6.1.11             Probability: relativising the frequencies …   132

6.1.12    The conclusion: the need for an on-line corpus    132

6.1.13    Comparison with other research …   133

6.2   Constructing the BKB …   137

6.2.1             Structural disambiguation    137

6.2.2    Identifying translation units …   139

6.2.3    Identifying referents …   140

6.3    Advantages and spin-offs of the BKB approach …   143

6.3.1            Basic advantages …   143

6.3.2    The spin-offs …   145
6.3.
3   Possible objections    146

 

Chapter  7.    Disambiguation   with   a   BKB:   Something   old   and   something   new, something borrowed...    149

7.1   Towards a new process architecture …   153

7.1.1    Selecting the translation units …   155

7.1.2    Challenging the selections …   156

7.1.3    Backtracking …   157

7.2   Examples of (simulated) BKB-based disambiguation   158

7.2.1            An example of lexical disambiguation …   159

7.2.2    Choosing between TL synonyms    182

7.2.3    Structural disambiguation    186

7.2.4    Functional disambiguation …   188

7.2.5    Referential disambiguation    190

7.3    Principles and techniques ….   193

7.3.1            TU selection by the Metataxor  … 193

7.3.2    Semantic coherence and the Examiner …   195

7.3.3    Evaluating referential relations    198

7.3.4    Evaluating functional relations …  198

7.3.5    Backtracking and semantic feedback …  200

7.4   A new look at the disambiguation dialogue   202

7.4.1    Structural ambiguity …  203

7.4.2    Referential ambiguity …  204

7.4.3    Functional ambiguity …   204

7.4.4    Lexical ambiguity …  205

Chapter 8. Towards intelligent disambiguation: Inferencing over the BKB   207

8.1    Inferring indirect referential relations  209

8.1.1            Inference based on explicit references  … 209

8.1.2    Inference in the absence of explicit references  … 212

 

8.2    Recognizing contradictions and inconsistencies …  218

8.3          Exploring deeper implications    223

8.4    The BKB as a basis for inference procedures  … 227

 

8.4.1            Discovering inference rules    227

8.4.2    Applying inference rules …  229

8.4.3            The knowledge representation …   230

Chapter 9.   Spin-off: BKBs, MKBs and other animals...    235

9.1           Other translation environments …  236

9.2    Monolingual knowledge banks …  241

9.3           Database applications …  243

In conclusion …   246
References    247
Index …   252