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The two papers included in this volume have developed from work with the CHILDES tools and the Media Editor in the two research projects, "Second language acquisition of German by Russian learners", sponsored by the Max Planck Institute for Psycholinguistics, Nijmegen, from 1998 to 1999 (directed by Ursula Stephany, University of Cologne, and Wolfgang Klein, Max Planck Institute for Psycholinguistics, Nijmegen) and "The age factor in the acquisition of German as a second language", sponsored by the German Science Foundation (DFG), Bonn, since 2000 (directed by Ursula Stephany, University of Cologne, and Christine Dimroth, Max Planck Institute for Psycholinguistics, Nijmegen). The CHILDES Project has been developed and is being continuously improved at Carnegie Mellon University, Pittsburgh, under the supervision of Brian MacWhinney. Having used the CHILDES tools for more than ten years for transcribing and analyzing Greek child data there it was no question that I would also use them for research into the acquisition of German as a second language and analyze the big amount of spontaneous speech gathered from two Russian girls with the help of the CLAN programs. When in the spring of 1997, Steven Gillis from the University of Antwerp (in collaboration with Gert Durieux) developed a lexicon-based automatic coding system based on the CLAN program MOR and suitable for coding languages with richer morphologies than English, such as Modern Greek. Coding huge amounts of data then became much quicker and more comfortable so that I decided to adopt this system for German as well. The paper "Working with the CHILDES Tools" is based on two earlier manuscripts which have grown out of my research on Greek child language and the many CHILDES workshops taught in Germany, Greece, Portugal, and Brazil over the years. Its contents have now been adapted to the requirements of research into the acquisition of German as a second language and for use on Windows.
In this paper we show an approach to the customization of GermaNet to the German HPSG grammar lexicon developed in the Verbmobil project. GermaNet has a broad coverage of the German base vocabulary and fine-grained semantic classification; while the HPSG grammar lexicon is comparatively small und has a coarse-grained semantic classification. In our approach, we have developed a mapping algorithm to relate the synsets in GermaNet with the semantic sorts in HPSG. The evaluation result shows that this approach is useful for the lexical extension of our deep grammar development to cope with real-world text understanding.
This paper proposes a corpus encoding standard that meets the needs of linguistic research using a variety of linguistic data structures. The standard was developed in SFB 441, a research project at the University of Tuebingen. The principal concern of SFB 441 are the empirical data structures which feed into linguistic theory building. SFB 441 consists of several projects, most of which are building corpora to empirically investigate various linguistic phenomena in various languages (e.g. modal verbs in German, forms of address and politeness in Russian). These corpora will form the components of the "Tuebingen collection of reusable, empirical, linguistic data structures (TUSNELDA)". The TUSNELDA annotation standard aims at providing a uniform encoding scheme for all subcorpora and texts of TUSNELDA such that they can be processed with uniform standardized tools. To guarantee maximal reusability we use XML for encoding. Previous SGML standards for text encoding were provided by the Text Encoding Initiative (TEI) and the Expert Advisory Group on Language Engineering Standards (Corpus Encoding Standard, CES). The TUSNELDA standard is based on TEI and XCES (XML version of CES) but takes into account the specific needs of the SFB projects, i.e. the peculiarities of the examined languages and linguistic phenomena.
Existing analyses of German scrambling phenomena within TAG-related formalisms all use non-local variants of TAG. However, there are good reasons to prefer local grammars, in particular with respect to the use of the derivation structure for semantics. Therefore this paper proposes to use local TDGs, a TAG-variant generating tree descriptions that shows a local derivation structure. However the construction of minimal trees for the derived tree descriptions is not subject to any locality constraint. This provides just the amount of non-locality needed for an adequate analysis of scrambling. To illustrate this a local TDG for some German scrambling data is presented.
In this paper, we investigate the role of sub-optimality in training data for part-of-speech tagging. In particular, we examine to what extent the size of the training corpus and certain types of errors in it affect the performance of the tagger. We distinguish four types of errors: If a word is assigned a wrong tag, this tag can belong to the ambiguity class of the word (i.e. to the set of possible tags for that word) or not; furthermore, the major syntactic category (e.g. "N" or "V") can be correctly assigned (e.g. if a finite verb is classified as an infinitive) or not (e.g. if a verb is classified as a noun). We empirically explore the decrease of performance that each of these error types causes for different sizes of the training set. Our results show that those types of errors that are easier to eliminate have a particularly negative effect on the performance. Thus, it is worthwhile concentrating on the elimination of these types of errors, especially if the training corpus is large.
We present a solution for the representation of Japanese honorifical information in the HPSG framework. Basically, there are three dimensions of honorification. We show that a treatment is necessary that involves both the syntactic and the contextual level of information. The japanese grammar is part of a machine translation system.
This paper proposes a compositional semantics for lexicalized tree adjoining grammars (LTAG). Tree-local multicompnent derivations allow seperation of semantiv contribution of a lexical item into one component contributing to the predicate argument structure and second a component contributing to scope semantics. Based on this idea a syntx-semantics interface is presented where the compositional semantics depends only on the derivation structure. It is shown that the derivation structure allows an appropriate amount of underspecification. This is illustrated by investigating underspecified representations for quantifier scpoe ambiguities and related phenomena such as adjunct scope and island constraints.
Particles fullfill several distinct central roles in the Japanese language. They can mark arguments as well as adjuncts, can be functional or have semantic functions. There is, however, no straightforward matching from particles to functions, as, e.g., 'ga' can mark the subject, the object or the adjunct of a sentence. Particles can cooccur. Verbal arguments that could be identified by particles can be eliminated in the Japanese sentence. And finally, in spoken language particles are often omitted. A proper treatment of particles is thus necessary to make an analysis of Japanese sentences possible. Our treatment is based on an empirical investigation of 800 dialogues. We set up a type hierarchy of particles motivated by their subcategorizational and modificational behaviour. This type hierarchy is part of the Japanese syntax in VERBMOBIL.
In syntax, the trend nowadays is towards lexicalized grammar formalisms. It is now widely accepted that dividing words into wordclasses may serve as a laborsaving mechanism - but at the same time, it discards all detailed information on the idiosyncratic behavior of words. And that is exactly the type of information that may be necessary in order to parse a sentence. For learning approaches, however, lexicalized grammars represent a challenge for the very reason that they include so much detailed and specific information, which is difficult to learn. This paper will present an algorithm for learning a link grammar of German. The problem of data sparseness is tackled by using all the available information from partial parses as well as from an existing grammar fragment and a tagger. This is a report about work in progress so there are no representative results available yet.