PhD thesis - School of Informatics - University of Edinburgh

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Chapter 3. Tracking English Inclusions in German 71 Domain Method Accuracy Precision Recall F-score Internet Baseline 93.95% - - - Lexicon module 95.09% 90.57% 23.04% 36.74 Search engine module 96.60% 68.82% 81.02% 74.43 Core system 97.47% 90.60% 66.32% 76.58 Full system 98.25% 92.75% 77.37% 84.37 Space Baseline 96.99% - - - Lexicon module 97.57% 77.78% 28.87% 42.11 Search engine module 95.62% 40.71% 97.11% 57.37 Core system 99.05% 84.85% 84.33% 84.59 Full system 99.45% 89.19% 93.61% 91.35 EU Baseline 99.69% - - - Lexicon module 99.69% 47.06% 38.10% 42.11 Search engine module 96.94% 6.99% 88.10% 12.96 Core system 98.41% 10.57% 66.67% 18.24 Full system 99.78% 59.26% 76.19% 66.67 Table 3.9: Evaluation of the lexicon and search engine modules compared to the core and full systems as well as the baseline.
Chapter 3. Tracking English Inclusions in German 72 The core English inclusion classifier essentially combines a high precision lexicon module with a high recall search engine module. This is achieved by first running the lexicon module to classify all known words. Subsequently, the search engine module only processes unknown words, namely those tokens that are not classified by the lexicon module. A token which is not resolved by this combined classification process is considered not to be an English inclusion by default. The combined core system outperforms the individual lexicon and search engine modules both for the internet and space travel data with F-scores of 76.58 and 84.59, respectively. Both of these domains contain considerably large numbers of English inclusions. For the EU data, which only contains very few English inclusions, the lexicon module was only outperformed by the full system due to the additional post-processing. One of the errors that seriously decreased the performance of the core system was made by the search engine module. It recognised the abbreviation EU as English. This error was corrected by means of abbreviation post-processing described in Section 3.3.5. Compared to the core system, the full English inclusion classifier involves a final post-processing stage as well as a document consistency check which are evaluated in more detail in Sections 3.4.2.3 and 3.4.2.4. The full system resulted in overall best F-scores for all three domains (Internet: F=84.37, Space: F=91.35, EU: F=66.67). 3.4.2.2 Web Search versus Corpus Search In order to understand the merit of the search engine module and the amount of data it can access better, the search engine module was replaced with a corpus search module that determines relative token frequencies based on fixed corpora. Here, the language classification is essentially based on real corpus frequencies rather than estimated web corpus frequencies. Language identification is simply conducted as a result of the higher relative frequency (rf) of a token (t) for a given corpus (C) in a particular language (L) and calculated as the actual frequency of a token in the corpus normalised by the corpus size (N). r f C(L)(t) = f C(L)(t) N C(L) (3.3)
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Automatic Detection of English Incl
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these parsers with the annotation-f
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Declaration I declare that this the
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3.3.5 Post-processing Module . . .
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A.2.2 Kappa Coefficient . . . . . .
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5.6 Average relative token frequenc
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3.16 Most frequent English inclusio
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Chapter 1. Introduction 2 siderable
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Chapter 1. Introduction 4 Chapter 3
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Chapter 1. Introduction 6 1.1 Relat
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Chapter 2. Background and Theory 8
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Chapter 6 Other Potential Applicati
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Chapter 6. Other Potential Applicat
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Chapter 7 Conclusions and Future Wo
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Chapter 7. Conclusions and Future W
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Appendix A. Evaluation Metrics and
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Appendix B. Guidelines for Annotati
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Appendix C TIGER Tags and Labels C.
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Appendix C. TIGER Tags and Labels 1
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Appendix C. TIGER Tags and Labels 1
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Bibliography 198 Andersen, G. (2005
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Bibliography 200 Bresnan, J. (2001)
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Bibliography 202 Damashek, M. (1995
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Bibliography 204 Finkel, J., Dingar
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Bibliography 206 Hachey, B., Alex,
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Bibliography 208 Kirkness, A. (1984
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Bibliography 210 and Technology (In
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Bibliography 212 Poplack, S. (1988)
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Bibliography 214 Sokol, D. K. (2000
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Bibliography 216 Yang, W. (1990). A
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PhD thesis - School of Informatics - University of Edinburgh

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