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In this feasibility study we aim at contributing at the practical use of domain ontologies for hypertext classification by introducing an algorithm generating potential keywords. The algorithm uses structural markup information and lemmatized word lists as well as a domain ontology on linguistics. We present the calculation and ranking of keyword candidates based on ontology relationships, word position, frequency information, and statistical significance as evidenced by log-likelihood tests. Finally, the results of our machine-driven classification are validated empirically against manually assigned keywords.
In this paper, we deal with register-driven variation from a probabilistic perspective, as proposed in Schäfer, Bildhauer, Pankratz, Müller (2022). We compare two approaches to analyse this variation within HPSG. On the one hand, we consider a multiple-grammar approach and combine it with the architecture proposed in the CoreGram project Müller (2015) - discussing its advantages and disadvantages. On the other hand, we take into account a single-grammar approach and argue that it appears to be superior due to its computational efficiency and cognitive plausibility.
Generative lexicalized parsing models, which are the mainstay for probabilistic parsing of English, do not perform as well when applied to languages with different language-specific properties such as free(r) word order or rich morphology. For German and other non-English languages, linguistically motivated complex treebank transformations have been shown to improve performance within the framework of PCFG parsing, while generative lexicalized models do not seem to be as easily adaptable to these languages. In this paper, we show a practical way to use grammatical functions as first-class citizens in a discriminative model that allows to extend annotated treebank grammars with rich feature sets without having to suffer from sparse data problems. We demonstrate the flexibility of the approach by integrating unsupervised PP attachment and POS-based word clusters into the parser.
The compilation of terminological vocabularies plays a central role in the organization and retrieval of scientific texts. Both simple keyword lists as well as sophisticated modellings of relationships between terminological concepts can make a most valuable contribution to the analysis, classification, and finding of appropriate digital documents, either on the Web or within local repositories. This seems especially true for long-established scientific fields with various theoretical and historical branches, such as linguistics, where the use of terminology within documents from different origins is sometimes far from being consistent. In this short paper, we report on the early stages of a project that aims at the re-design of an existing domain-specific KOS for grammatical content grammis. In particular, we deal with the terminological part of grammis and present the state-of-the-art of this online resource as well as the key re-design principles. Further, we propose questions regarding ramifications of the Linked Open Data and Semantic Web approaches for our re-design decisions.
MULLE is a tool for language learning that focuses on teaching Latin as a foreign language. It is aimed for easy integration into the traditional classroom setting and syllabus, which makes it distinct from other language learning tools that provide standalone learning experience. It uses grammar-based lessons and embraces methods of gamification to improve the learner motivation. The main type of exercise provided by our application is to practice translation, but it is also possible to shift the focus to vocabulary or morphology training.
In this paper we investigate the problem of grammar inference from a different perspective. The common approach is to try to infer a grammar directly from example sentences, which either requires a large training set or suffers from bad accuracy. We instead view it as a problem of grammar restriction or sub-grammar extraction. We start from a large-scale resource grammar and a small number of examples, and find a sub-grammar that still covers all the examples. To do this we formulate the problem as a constraint satisfaction problem, and use an existing constraint solver to find the optimal grammar. We have made experiments with English, Finnish, German, Swedish and Spanish, which show that 10–20 examples are often sufficient to learn an interesting domain grammar. Possible applications include computer-assisted language learning, domain-specific dialogue systems, computer games, Q/A-systems, and others.
An interactive, dynamic electronic dictionary aimed at text production should guide the user in innovative ways, especially in respect of difficult, complicated or confusing issues. This paper proposes a design for bilingual dictionaries intended to guide users in text production; we focus on complex phenomena of the interaction between lexis and grammar. It will be argued that a dictionary aimed at guiding the user in lexical selection should implement a type of “decision algorithm”. In addition, it should flag incorrect solutions and should warn against possible wrong generalisations of (foreign) language learners. Our proposals will be illustrated with examples from several languages, as the design principles are generally applicable. The copulative construction which is regarded as the most complicated grammatical structure in Northern Sotho will be analyzed in more detail and presented as a case in point.
In this paper we present work in developing a computerized grammar for the Latin language. It demonstrates the principles and challenges in developing a grammar for a natural language in a modern grammar formalism. The grammar presented here provides a useful resource for natural language processing applications in different fields. It can be easily adopted for language learning and use in language technology for Cultural Heritage like translation applications or to support post-correction of document digitization.
To reach even language users not acquainted to the use of grammars the Institut für Deutsche Sprache in Mannheim (Germany) looked for new ways to handle grammatical problems. Instead of confronting users with abstractions frequent difficulties of German grammar are introduced in form of exemplary questions like „Which form should be used or preferred: Anfang dieses Jahre or Anfang diesen Jahres? Looking through the long list of such questions even laymen may find solutions of grammatical problems they might not be able to formulate as such.
Seit Mitte der 1990er Jahre wird am Institut für deutsche Sprache (IDS) in Mannheim erforscht, wie der hochkomplexe Gegenstandsbereich „Grammatik“ unter Ausnutzung hypertextueller Navigationsstrukturen wissenschaftlich fundiert und anschaulich vermittelt werden kann. Eine zentrale Bedeutung kommt folglich einer konsistenten, theorieübergreifenden Vernetzung sämtlicher Textinhalte zu. Um eine automatisierbare Bezugnahme zwischen mit unterschiedlichem terminologischem Vokabular formulierten, aber das gleiche sprachliche Phänomen beschreibenden Inhalten zu befördern, bildet eine onomasiologisch konzipierte Terminologiedatenbank das Rückgrat des Online-Systems. Der Beitrag beschreibt Konzeption und Aufbau der skizzierten linguistischen Fachterminologie.
We present a language learning application that relies on grammars to model the learning outcome. Based on this concept we can provide a powerful framework for language learning exercises with an intuitive user interface and a high reliability. Currently the application aims to augment existing language classes and support students by improving the learner attitude and the general learning outcome. Extensions beyond that scope are promising and likely to be added in the future.
This paper presents C-WEP, the Collection of Writing Errors by Professionals Writers of German. It currently consists of 245 sentences with grammatical errors. All sentences are taken from published texts. All authors are professional writers with high skill levels with respect to German, the genres, and the topics. The purpose of this collection is to provide seeds for more sophisticated writing support tools as only a very small proportion of those errors can be detected by state-of-the-art checkers. C-WEP is annotated on various levels and freely available.