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Chat-Bot-Kit: A web-based tool to simulate text-based interactions between humans and with computers ...
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German compound splitting using the compound productivity of morphemes ...
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Building a Corpus from Handwritten Picture Postcards: Transcription, Annotation and Part-of-Speech Tagging
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In: Sugisaki, Kyoko; Wiedmer, Nicolas; Hausendorf, Heiko (2018). Building a Corpus from Handwritten Picture Postcards: Transcription, Annotation and Part-of-Speech Tagging. In: 11th edition of the Language Resources and Evaluation Conference, Miyazaki, Japan, May 2018, s.n. (2018)
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Supertagging for Domain Adaptation: An Approach with Law Texts
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In: Sugisaki, Kyoko (2017). Supertagging for Domain Adaptation: An Approach with Law Texts. In: The 16th International Conference on Artificial Intelligence and Law, London, 12 June 2017 - 16 June 2017. (2017)
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Word and sentence segmentation in german: Overcoming idiosyncrasies in the use of punctuation in private communication
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In: Sugisaki, Kyoko (2017). Word and sentence segmentation in german: Overcoming idiosyncrasies in the use of punctuation in private communication. In: 27th International Conference, GSCL 2017, Berlin, September 2017, s.n. (2017)
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Building a Corpus of Multi-lingual and Multi-format International Investment Agreements ...
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Automatic Annotation and Assessment of Syntactic Structures in Law Texts Combining Rule-Based and Statistical Methods
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In: Sugisaki, Kyoko. Automatic Annotation and Assessment of Syntactic Structures in Law Texts Combining Rule-Based and Statistical Methods. 2016, University of Zurich, Faculty of Arts. (2016)
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Abstract:
In this thesis, I investigate and develop methods for automatically analyzing and assessing German syntactic structures in domain-specific texts. As domain-specific texts, I use Swiss German-language law texts. The automatic annotation of syntactic structures has long been studied in the research on natural language processing. Supervised statistical methods are regarded as state-of-the-art parsing methods, which are accurate but biased by the type of text. Consequently, the accuracy of statistical parsers decreases if they are used on domain-specific texts. The problem of domain bias in syntactic annotation should be solved if it directly affects the accuracy of an application. The syntactic assessment that I develop in this thesis is such an application that requires high accuracy of syntactic annotation. An effective solution to this problem would be the manual annotation of a large portion of the required domain texts. However, it is not feasible in practice because manual linguistic annotation is extremely labor intensive. To overcome this problem, I develop syntactic annotation methods that do not require the manual annotation of a large portion of the domain texts. The goal of this thesis is that the annotation accuracy on domain-specific texts is so high that it can be used for the application. For the automatic syntactic assessment, I demonstrate a novel approach to model domain-specific style choice by combining rule-based and statistical methods. In the rule-based approach, I present a method that automatically detects the violations of style rules in legislative style guidelines. In the statistical approach, domain-specific writing style is defined in terms of stylistic choice between syntactic alternations. The syntactic selection is statistically modeled by classifying syntactic alternatives according to their syntactic complexity. The syntactic assessment requires automatic syntactic annotation. For the automatic syntactic annotation, I present a linguistically motivated hybrid supertagger that analyzes topological dependency grammar relations in the German language. In this thesis, supertagging problems are seen as morphosyntactic ambiguity and syntactic resolution. Depending on the linguistic phenomena, the ambiguity is resolved by applying a rule-based and statistical tagging method: Morphological and syntactic hard constraints are applied in a constraint grammar approach. In contrast, lexical, semantic, and pragmatic soft and multivariate constraints are integrated into a conditional random fields model. The main contribution of this thesis to the study of natural language processing is to show that a linguistically motivated annotation method is a viable approach to achieving a high performance of syntactic analysis with a few hundreds of manually annotated sentences from the domain.
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Keyword:
000 Computer science; 410 Linguistics; Institute of Computational Linguistics; knowledge & systems; UZH Dissertations
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URL: https://www.zora.uzh.ch/id/eprint/126637/1/diss.pdf
https://www.zora.uzh.ch/id/eprint/126637/
https://doi.org/10.5167/uzh-126637
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Towards Data-Driven Style Checking: An Example for Law Texts
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In: Sugisaki, Kyoko (2016). Towards Data-Driven Style Checking: An Example for Law Texts. In: 29th International Conference on Legal Knowledge and Information Systems (Jurix), Nice, December 2016, s.n. (2016)
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Incremental morphosyntactic disambiguation of nouns in German-language law texts ...
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Incremental morphosyntactic disambiguation of nouns in German-language law texts
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In: Sugisaki, Kyoko; Höfler, Stefan (2013). Incremental morphosyntactic disambiguation of nouns in German-language law texts. In: ESSLLI-13 Workshop on Extrinsic Parse Improvement (EPI), Düsseldorf, 12 August 2013 - 16 August 2013. (2013)
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From drafting guideline to error detection: Automating style checking for legislative texts ...
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From drafting guideline to error detection: Automating style checking for legislative texts
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In: Höfler, Stefan; Sugisaki, Kyoko (2012). From drafting guideline to error detection: Automating style checking for legislative texts. In: EACL 2012 Workshop on Computational Linguistics and Writing, Avignon, France, 23 April 2012 - 23 April 2012, 9-18. (2012)
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Detecting legal definitions for automated style checking in draft laws
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In: Höfler, Stefan; Bünzli, Alexandra; Sugisaki, Kyoko (2011). Detecting legal definitions for automated style checking in draft laws. Technical Reports in Computational Linguistics CL-2011.01, University of Zurich. (2011)
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