PhD thesis - School of Informatics - University of Edinburgh

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Chapter 3. Tracking English Inclusions in German 55 LEXICON 00 11 00 11 00 11 00 11 00 11 00 11 00 11 00 11 00 11 00 11 00 11 HTML 00 11 00 11 00 11 00 11 00 11 00 11 TIDY TOKENISER POS TAGGER POST−PROCESSING 00 11 00 1100 11 00 1100 1100 11 00 1100 1100 11 00 1100 1100 11 00 1100 1100 11 00 1100 11 00 11 WWW CONSISTENCY CHECK LANGUAGE CLASSIFICATION Figure 3.1: System architecture of the English inclusion classifier.
Chapter 3. Tracking English Inclusions in German 56 3.3.1 Processing Paradigm The underlying processing paradigm of the English inclusion classifier is XML-based. As a markup language for NLP tasks, XML is expressive and flexible yet constrain- able. Furthermore, there exists a wide range of XML-based tools for NLP applications which lend themselves to a modular, pipelined approach to processing whereby linguistic knowledge is computed and added incrementally as XML annotations. More- over, XML’s character encoding capabilities facilitate multilingual processing. As il- lustrated in Figure 3.1, the system for processing German text is essentially a UNIX pipeline which converts HTML files to XML and applies a sequence of modules: a pre- processing module for tokenisation and POS tagging, followed by a lexicon lookup, a search engine module, post-processing and an optional document consistency check which all add linguistic markup and classify tokens as either German or English. The pipeline is composed partly of calls to LT-TTT2 and LT-XML2 (Grover et al., 2006) 4 for tokenisation and sentence splitting. In addition, non-XML public-domain tools such as the TnT tagger (Brants, 2000b) were integrated and their output incorporated into the XML markup. The primary advantage of this architecture is the ability to integrate the output of already existing tools with that of new modules specifically tailored to the task in an organised fashion. The XML output can be searched to find specific instances or to acquire counts of occurrences using the LT-XML2 tools. 3.3.2 Pre-processing Module All downloaded Web documents are first of all cleaned up using TIDY 5 to remove HTML markup and any non-textual information and then converted into XML. Alter- natively, the input into the classifier can be in simple text format which is subsequently converted into XML format. The resulting XML pages simply contain the textual information of each article. Subsequently, all documents are passed through a series of pre-processing steps implemented using the LT-XML2 and LT-TTT2 tools (Grover et al., 2006) with the output of each step encoded in XML. Two rule-based grammars which were developed specifically for German are used 4 These tools are improved upgrades of the LT-TTT and LT-XML toolsets (Grover et al., 2000; Thompson et al., 1997) and are available under GPL as LT-TTT2 and LT-XML2 at: http://www.ltg.ed.ac. uk. 5http://tidy.sourceforge.net
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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 5 Parsing English Inclusion
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Chapter 5. Parsing English Inclusio
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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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