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Warum spielt in Bernhard Waldenfels’ Phänomenologie des Fremden das Werk Robert Musils, genauer, sein Roman Der Mann ohne Eigenschaften eine so prominente Rolle? Diese Frage wird am Ende des vorliegenden Beitrags immer noch eine Frage bleiben, wiewohl in mehreren Anläufen versucht werden soll, sie zu spezifizieren und Ansätze zu möglichen Antworten anzubieten. Bevor jedoch verschiedene Argumente angehäuft werden, möchte ich die Fragestellung selbst im Lichte des Tagungsthemas umkreisen. In Zeiten, in denen sich die Literaturwissenschaft immer noch dem fachlichen Legitimationsdruck ausgesetzt sieht, und diesem Druck dadurch abzuhelfen versucht, eine Neuorientierung in kulturwissenschaftliche Gebiete à la Bologna vorzunehmen, bieten sich solche Grenzerweiterungsexperimente mit einer Selbstverständlichkeit an, die eine Öffnung zu Nachbardisziplinen begünstigen. ...
Um die Vorwürfe zu entkräften, die gegen sein Stück Der Müll, die Stadt und der Tod erhoben wurden, gab Rainer Werner Fassbinder folgende Inhaltsangabe: "Die Stadt läßt die vermeintlich notwendige Dreckarbeit von einem, und das ist besonders infam, tabuisierten Juden tun, und die Juden sind seit 1945 in Deutschland tabuisiert, was am Ende zurückschlagen muß, denn Tabus, darüber sind sich doch wohl alle einig, führen dazu, daß das Tabuisierte, Dunkle, Geheimnisvolle Angst macht und endlich Gegner findet." Fassbinder äußert sich hier, als hätte er ein Stück im Stil von Brechts Rund und Spitzköpfen geschrieben. Doch gerade er hat dem Dunklen, Geheimnisvollen, Angstmachenden, das er vom Tabu ausgehen sieht, selbständige Gestalt erst gegeben, als er die Figur des "reichen Juden" in den Mittelpunkt seines Stücks rückte. "Dieser Jude", sagt Fassbinder, "ist reich, ist Häusermakler, trägt dazu bei, die Städte zuungunsten der Menschen zu verändern; er führt aber letztlich doch nur Dinge aus, die von anderen zwar konzipiert wurden, aber deren Verwirklichung man konsequent einem überläßt, der durch Tabuisierung unangreifbar scheint." Während die anderen, die Mächtigen der Stadtverwaltung, mit der "Dreckarbeit" jeweils einen Zweck verfolgen, führt der Jude sie um ihrer selbst willen aus. Davon handeln seine Monologe: "Es muß mir egal sein, ob Kinder weinen, ob Alte, Gebrechliche leiden. Es muß mir egal sein. Und das Wutgeheul mancher, das überhör ich ganz einfach. Was soll ich auch sonst. [...] Soll meine Seele geradestehen für die Beschlüsse anderer, die ich nur ausführe mit dem Profit, den ich brauche, um mir das leisten zu können, was ich brauche. Was brauch ich? Brauche, brauche – seltsam, wenn man ein Wort ganz oft sagt, verliert es den Sinn, den es ohnehin nur zufällig hat. Die Stadt braucht den skrupellosen Geschäftsmann, der ihr ermöglicht sich zu verändern. Sie hat ihn gefälligst zu schützen." (S. 681). ...
In the past, a divide could be seen between ’deep’ parsers on the one hand, which construct a semantic representation out of their input, but usually have significant coverage problems, and more robust parsers on the other hand, which are usually based on a (statistical) model derived from a treebank and have larger coverage, but leave the problem of semantic interpretation to the user. More recently, approaches have emerged that combine the robustness of datadriven (statistical) models with more detailed linguistic interpretation such that the output could be used for deeper semantic analysis. Cahill et al. (2002) use a PCFG-based parsing model in combination with a set of principles and heuristics to derive functional (f-)structures of Lexical-Functional Grammar (LFG). They show that the derived functional structures have a better quality than those generated by a parser based on a state-of-the-art hand-crafted LFG grammar. Advocates of Dependency Grammar usually point out that dependencies already are a semantically meaningful representation (cf. Menzel, 2003). However, parsers based on dependency grammar normally create underspecified representations with respect to certain phenomena such as coordination, apposition and control structures. In these areas they are too "shallow" to be directly used for semantic interpretation. In this paper, we adopt a similar approach to Cahill et al. (2002) using a dependency-based analysis to derive functional structure, and demonstrate the feasibility of this approach using German data. A major focus of our discussion is on the treatment of coordination and other potentially underspecified structures of the dependency data input. F-structure is one of the two core levels of syntactic representation in LFG (Bresnan, 2001). Independently of surface order, it encodes abstract syntactic functions that constitute predicate argument structure and other dependency relations such as subject, predicate, adjunct, but also further semantic information such as the semantic type of an adjunct (e.g. directional). Normally f-structure is captured as a recursive attribute value matrix, which is isomorphic to a directed graph representation. Figure 5 depicts an example target f-structure. As mentioned earlier, these deeper-level dependency relations can be used to construct logical forms as in the approaches of van Genabith and Crouch (1996), who construct underspecified discourse representations (UDRSs), and Spreyer and Frank (2005), who have robust minimal recursion semantics (RMRS) as their target representation. We therefore think that f-structures are a suitable target representation for automatic syntactic analysis in a larger pipeline of mapping text to interpretation. In this paper, we report on the conversion from dependency structures to fstructure. Firstly, we evaluate the f-structure conversion in isolation, starting from hand-corrected dependencies based on the TüBa-D/Z treebank and Versley (2005)´s conversion. Secondly, we start from tokenized text to evaluate the combined process of automatic parsing (using Foth and Menzel (2006)´s parser) and f-structure conversion. As a test set, we randomly selected 100 sentences from TüBa-D/Z which we annotated using a scheme very close to that of the TiGer Dependency Bank (Forst et al., 2004). In the next section, we sketch dependency analysis, the underlying theory of our input representations, and introduce four different representations of coordination. We also describe Weighted Constraint Dependency Grammar (WCDG), the dependency parsing formalism that we use in our experiments. Section 3 characterises the conversion of dependencies to f-structures. Our evaluation is presented in section 4, and finally, section 5 summarises our results and gives an overview of problems remaining to be solved.
Using a qualitative analysis of disagreements from a referentially annotated newspaper corpus, we show that, in coreference annotation, vague referents are prone to greater disagreement. We show how potentially problematic cases can be dealt with in a way that is practical even for larger-scale annotation, considering a real-world example from newspaper text.
In this paper, we investigate the usefulness of a wide range of features for their usefulness in the resolution of nominal coreference, both as hard constraints (i.e. completely removing elements from the list of possible candidates) as well as soft constraints (where a cumulation of violations of soft constraints will make it less likely that a candidate is chosen as the antecedent). We present a state of the art system based on such constraints and weights estimated with a maximum entropy model, using lexical information to resolve cases of coreferent bridging.
In recent years, research in parsing has extended in several new directions. One of these directions is concerned with parsing languages other than English. Treebanks have become available for many European languages, but also for Arabic, Chinese, or Japanese. However, it was shown that parsing results on these treebanks depend on the types of treebank annotations used. Another direction in parsing research is the development of dependency parsers. Dependency parsing profits from the non-hierarchical nature of dependency relations, thus lexical information can be included in the parsing process in a much more natural way. Especially machine learning based approaches are very successful (cf. e.g.). The results achieved by these dependency parsers are very competitive although comparisons are difficult because of the differences in annotation. For English, the Penn Treebank has been converted to dependencies. For this version, Nivre et al. report an accuracy rate of 86.3%, as compared to an F-score of 92.1 for Charniaks parser. The Penn Chinese Treebank is also available in a constituent and a dependency representations. The best results reported for parsing experiments with this treebank give an F-score of 81.8 for the constituent version and 79.8% accuracy for the dependency version. The general trend in comparisons between constituent and dependency parsers is that the dependency parser performs slightly worse than the constituent parser. The only exception occurs for German, where F-scores for constituent plus grammatical function parses range between 51.4 and 75.3, depending on the treebank, NEGRA or TüBa-D/Z. The dependency parser based on a converted version of Tüba-D/Z, in contrast, reached an accuracy of 83.4%, i.e. 12 percent points better than the best constituent analysis including grammatical functions.
This paper profiles significant differences in syntactic distribution and differences in word class frequencies for two treebanks of spoken and written German: the TüBa-D/S, a treebank of transliterated spontaneous dialogues, and the TüBa-D/Z treebank of newspaper articles published in the German daily newspaper die tageszeitung´(taz). The approach can be used more generally as a means of distinguishing and classifying language corpora of different genres.
This paper presents an approach to the question whether it is possible to construct a parser based on ideas from case-based reasoning. Such a parser would employ a partial analysis of the input sentence to select a (nearly) complete syntax tree and then adapt this tree to the input sentence. The experiments performed on German data from the Tüba-D/Z treebank and the KaRoPars partial parser show that a wide range of levels of generality can be reached, depending on which types of information are used to determine the similarity between input sentence and training sentences. The results are such that it is possible to construct a case-based parser. The optimal setting out of those presented here need to be determined empirically.
This paper presents a comparative study of probabilistic treebank parsing of German, using the Negra and TüBa-D/Z treebanks. Experiments with the Stanford parser, which uses a factored PCFG and dependency model, show that, contrary to previous claims for other parsers, lexicalization of PCFG models boosts parsing performance for both treebanks. The experiments also show that there is a big difference in parsing performance, when trained on the Negra and on the TüBa-D/Z treebanks. Parser performance for the models trained on TüBa-D/Z are comparable to parsing results for English with the Stanford parser, when trained on the Penn treebank. This comparison at least suggests that German is not harder to parse than its West-Germanic neighbor language English.
This report explores the question of compatibility between annotation projects including translating annotation formalisms to each other or to common forms. Compatibility issues are crucial for systems that use the results of multiple annotation projects. We hope that this report will begin a concerted effort in the field to track the compatibility of annotation schemes for part of speech tagging, time annotation, treebanking, role labeling and other phenomena.