Semantik der Adjektive des Deutschen

Hundsnurscher, Franz; Splett, Jochen

doi:10.1007/978-3-322-87624-9

Cited by 4 publications

(2 citation statements)

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“…WordNet lacks coarse-grained semantic categories for adjectives. To divide adjectives into groups, Tsvetkov et al (2014) use 13 top-level classes from the adapted taxonomy of Hundsnurscher and Splett (1982), which is incorporated in GermaNet (Hamp and Feldweg, 1997). For example, the top-level classes in GermaNet include: adj.feeling (e.g., willing, pleasant, cheerful); adj.substance (e.g., dry, ripe, creamy); adj.spatial (e.g., adjacent, gigantic).…”

Section: Feature Extractionmentioning

confidence: 99%

Metaphor Detection with Cross-Lingual Model Transfer

Tsvetkov

Boytsov

Gershman

et al. 2014

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

176

209

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We show that it is possible to reliably discriminate whether a syntactic construction is meant literally or metaphorically using lexical semantic features of the words that participate in the construction. Our model is constructed using English resources, and we obtain state-of-the-art performance relative to previous work in this language. Using a model transfer approach by pivoting through a bilingual dictionary, we show our model can identify metaphoric expressions in other languages. We provide results on three new test sets in Spanish, Farsi, and Russian. The results support the hypothesis that metaphors are conceptual, rather than lexical, in nature.

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Section: Feature Extractionmentioning

confidence: 99%

Metaphor Detection with Cross-Lingual Model Transfer

Tsvetkov

Boytsov

Gershman

et al. 2014

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

176

209

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show abstract

“…The data collection involved three types of matrices: one for verbal constructions (see Table 4), the second for adjectival constructions (see Table 6), and the other for nominal constructions (see Table 8). The former was constructed using the postulate of verbs (Viberg, 1983(Viberg, , 2014, while the latter was constructed using the premise of adjectives (Hundsnurscher, 1992(Hundsnurscher, , 2013, and the last one was constructed by using the hypothesis of nouns (Aikhenvald, 2017(Aikhenvald, , 2020. Second, annotation and classification.…”

Section: Methodsmentioning

confidence: 99%

Analyzing Prefix /me(N)-/ in the Indonesian Affixation: A Corpus-Based Morphology

Nugraha

2024

tpls

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This paper presents a corpus-based study of the prefix /me(N)-/ in Indonesian, a productive affix used to form predicative constructions. The analysis was based on the Indonesian – Leipzig Corpora Collection (ILCC). It explored the prefix’s distribution, functions, and productivity, focusing on its role in encoding semantic and syntactic features. The results showed that the prefix /me(N)-/ was predominantly used to derive verbs, accounting for over 68,7% at the mean value of 7,1. However, /me(N)-/ was also employed to derive adjectives, albeit less frequently (19.4%), at the mean value of 6,3, and about 12% of forming new words from noun stems (mean value was about 5,9). Semantically, the prefix can uniquely express causative (49,24% at a mean value of 43), instrumental (11,45% at a mean value of 10), reflexive (19,47 at a mean value of 17), possessive/state meanings (10,31% at a mean value of 9), and reciprocal (9,54% at a mean value of 8,3). Derived verbs with the prefix /me(N)-/ had syntactic functions influenced by their semantic meaning. Some of the most common and distinctive syntactic functions of /me(N)-/ are form monovalent (29,18% having a mean value of 27,33), bivalent (48,40% having a mean value of 45,33), and trivalent (22,42% having a mean value of 21). The study demonstrated that /me(N)-/ was highly productive. Future research could examine the cognitive and processing mechanisms involved in understanding /me(N)-/-derived words.

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A Review of Scene Visualization Based on Language Descriptions

Zeng

Mling

2009

2009 Sixth International Conference on Computer Graphics, Imaging and Visualization

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When dealing with computational models for integrating natural language and graphic representation, it is useful to examine theories of human visual perception and spatial language to discover what kind of processes and representation lie in between. This paper begins with a discussion of systems which have been implemented. It outlines related natural language processing technology and theories that involve in language based scene visualization. We then discuss the way can be used to integration of visual information for scene generation.

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Semantik der Adjektive des Deutschen

Cited by 4 publications

References 0 publications

Metaphor Detection with Cross-Lingual Model Transfer

Metaphor Detection with Cross-Lingual Model Transfer

Analyzing Prefix /me(N)-/ in the Indonesian Affixation: A Corpus-Based Morphology

A Review of Scene Visualization Based on Language Descriptions

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