Refine
Year of publication
- 2011 (167) (remove)
Document Type
- Part of a Book (78)
- Article (54)
- Book (12)
- Conference Proceeding (11)
- Part of Periodical (5)
- Contribution to a Periodical (3)
- Other (3)
- Review (1)
Keywords
- Deutsch (102)
- Korpus <Linguistik> (22)
- Computerunterstützte Lexikographie (14)
- Online-Wörterbuch (12)
- Wörterbuch (12)
- Grammatik (11)
- Interaktionsanalyse (11)
- Computerlinguistik (9)
- Konversationsanalyse (9)
- Internet (8)
-
Den Wald vor lauter Bäumen sehen - und andersherum: zum Verhältnis von 'Mustern' und 'Regeln'
(2011)
- Die Konstruktionsgrammatik setzt dem Begriff der konstruktiven Regel den des komplexen Musters entgegen, das in syntaktischen Generalisierungsprozessen analogisch erweitert wird. Der vorliegende Beitrag präsentiert eine solche musterbasierte Analyse von deutschen Konstruktionen mit lokativem Subjekt (Wiesen und Wälder wuchern vor Blumen und Kräutern) als Extension einer Reihe verwandter Konstruktionen mit kausaler und intensivierender Funktion, aus denen die lokative Variante mutmaßlich hervorgegangen ist. Die Analyse argumentiert, dass der umgebenden ,Ökologie‘ der Zielkonstruktion im sprachlichen Wissen der Sprecher eine zentrale Rolle für die Erklärung der attestierten Varianten zukommt, die in regelbasierten Zugängen als unmotivierte ,Ausnahmen‘ von allgemeinen Linkingprinzipien gelten müssen.
- Oscailt/Opening (2011)
-
Modelling and Processing Wordnets in OWL
(2011)
- In this contribution, we discuss and compare alternative options of modelling the entities and relations of wordnet-like resources in the Web Ontology Language OWL. Based on different modelling options, we developed three models of representing wordnets in OWL, i.e. the instance model, the dass model, and the metaclass model. These OWL models mainly differ with respect to the ontological Status of lexical units (word senses) and the synsets. While in the instance model lexical units and synsets are represented as individuals, in the dass model they are represented as classes; both model types can be encoded in the dialect OWL DL. As a third alternative, we developed a metaclass model in OWL FULL, in which lexical units and synsets are defined as metaclasses, the individuals of which are classes themselves. We apply the three OWL models to each of three wordnet-style resources: (1) a subset of the German wordnet GermaNet, (2) the wordnet-style domain ontology TermNet, and (3) GermaTermNet, in which TermNet technical terms and GermaNet synsets are connected by means of a set of “plug-in” relations. We report on the results of several experiments in which we evaluated the performance of querying and processing these different models: (1) A comparison of all three OWL models (dass, instance, and metaclass model) of TermNet in the context of automatic text-to-hypertext conversion, (2) an investigation of the potential of the GermaTermNet resource by the example of a wordnet-based semantic relatedness calculation.
-
Comparing word and syllable prominence rated by naïve listeners
(2011)
- Prominence has been widely studied on the word level and the syllable level. An extensive study comparing the two approaches is missing in the literature. This study investigates how word and syllable prominence relate to each other in German. We find that perceptual ratings based on the word level are more extreme than those based on the syllable level. The correlations between word prominence and acoustic features are greater than the correlations between syllable prominence and acoustic features.
-
Evaluating different rating scales for obtaining judgments of syllable prominence from naïve listeners
(2011)
- Streefkerk defines prominence as the perceptually outstanding parts in spoken language. An optimal rating scale for syllable prominence has not been found yet. This paper evaluates a 4-point, an 11-point, a 31-point, and a continuous scale for the rating of syllable prominence and gives support for scales using a higher number of levels. Priming effects found by Arnold, et al., could only be replicated using the 31-point scale.