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Mein Beitrag betrachtet einen Grundpfeiler jedes literaturwissenschaftlichen Seminars vor dem Hintergrund (nicht nur coronabedingter) Online-Lehre: Seminarlektüren. Texte zu lesen, zu diskutieren, für die weitere Seminararbeit zu verwenden, gehört zu den grundlegenden Tätigkeiten in literaturwissenschaftlichen Seminaren. Seminarlektüren umfassen dabei alle im Seminar gemeinsam gelesenen Texte: literarische Texte verschiedener Gattungen ebenso wie wissenschaftliche Textsorten als Sekundärliteratur. In der Hinsicht ist diese Reflexion nicht nur für die Arbeit in literaturwissenschaftlichen Seminaren gewinnbringend, sondern auch für sprachwissenschaftliche und didaktische Lehrveranstaltungen notwendig.
Syntactic coindexing restrictions are by now known to be of central importance to practical anaphor resolution approaches. Since, in particular due to structural ambiguity, the assumption of the availability of a unique syntactic reading proves to be unrealistic, robust anaphor resolution relies on techniques to overcome this deficiency. In this paper, two approaches are presented which generalize the verification of coindexing constraints to de cient descriptions. At first, a partly heuristic method is described, which has been implemented. Secondly, a provable complete method is specified. It provides the means to exploit the results of anaphor resolution for a further structural disambiguation. By rendering possible a parallel processing model, this method exhibits, in a general sense, a higher degree of robustness. As a practically optimal solution, a combination of the two approaches is suggested.
Quantitative Textanalyse wird oft mit empirischer Literaturwissenschaft verwechselt oder als Wörterzählen verniedlicht. Gerade in den Anfängen der Romanistik, als Linguistik und Literaturwissenschaft noch wesentlich enger verknüpft waren, wurde jedoch auch in der Textanalyse literarischer Werke mit Konkordanztabellen und anderen äußeren Strukturmerkmalen von Texten gearbeitet. Heute wird im Kontext der Digital Humanities in der Literaturwissenschaft versucht, Erkenntnisse aus dem Bereich der forensischen Linguistik und Autorschaftsattribution auch zur literarischen Stil- und Gattungsdiskussion zu verwenden. Die Methode der Stilometrie nutzt dabei vor allem das leicht zugängliche Tool stylo für das Statistikprogramm R, das von der Gruppe computational stylistics entwickelt wurde.
Der Workshop setzt sich aus folgenden Teilen zusammen:
1. Einführung in die quantitative Textanalyse im Kontext der Digital Humanities
2. Erläuterung der Funktionsweise von Stilometrie: mathematische Distanzmaße und statistische Verteilung
3. Anwendungsbeispiel mit stylo für R
In the last years, much effort went into the design of robust anaphor resolution algorithms. Many algorithms are based on antecedent filtering and preference strategies that are manually designed. Along a different line of research, corpus-based approaches have been investigated that employ machine-learning techniques for deriving strategies automatically. Since the knowledge-engineering effort for designing and optimizing the strategies is reduced, the latter approaches are considered particularly attractive. Since, however, the hand-coding of robust antecedent filtering strategies such as syntactic disjoint reference and agreement in person, number, and gender constitutes a once-for-all effort, the question arises whether at all they should be derived automatically. In this paper, it is investigated what might be gained by combining the best of two worlds: designing the universally valid antecedent filtering strategies manually, in a once-for-all fashion, and deriving the (potentially genre-specific) antecedent selection strategies automatically by applying machine-learning techniques. An anaphor resolution system ROSANA-ML, which follows this paradigm, is designed and implemented. Through a series of formal evaluations, it is shown that, while exhibiting additional advantages, ROSANAML reaches a performance level that compares with the performance of its manually designed ancestor ROSANA.
An anaphor resolution algorithm is presented which relies on a combination of strategies for narrowing down and selecting from antecedent sets for re exive pronouns, nonre exive pronouns, and common nouns. The work focuses on syntactic restrictions which are derived from Chomsky's Binding Theory. It is discussed how these constraints can be incorporated adequately in an anaphor resolution algorithm. Moreover, by showing that pragmatic inferences may be necessary, the limits of syntactic restrictions are elucidated.