Semantic Splitting of German Medical Compounds

Bretschneider, Claudia; Zillner, Sonja

doi:10.1007/978-3-319-24033-6_24

Cited by 2 publications

(3 citation statements)

References 6 publications

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“…She observed that splitting parameters should not necessarily be the same for translating in different directions. Bretschneider and Zillner (2015) compared the splitting performance between Koehn and Knight's (2003) two fillers and Langer's (1998) collection, illustrating the necessity of an exhaustive set of linking elements. Moreover, they showed that Langer's (1998) data is still not sufficient for domain-specific targets.…”

Section: Related Workmentioning

confidence: 99%

“…We would like to take this one step further by avoiding the usage of parallel data, which are known to be sparse and frequently domain-specific, while Bretschneider and Zillner (2015) showed that compounding morphology varies between different domains. Instead, we exploit lemmatized corpora and use word inflection as an approximation to compounding morphology.…”

Section: Introductionmentioning

confidence: 99%

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Towards Unsupervised and Language-independent Compound Splitting using Inflectional Morphological Transformations

Ziering¹,

Plas²

2016

Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

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In this paper, we address the task of languageindependent, knowledge-lean and unsupervised compound splitting, which is an essential component for many natural language processing tasks such as machine translation. Previous methods on statistical compound splitting either include language-specific knowledge (e.g., linking elements) or rely on parallel data, which results in limited applicability. We aim to overcome these limitations by learning compounding morphology from inflectional information derived from lemmatized monolingual corpora. In experiments for Germanic languages, we show that our approach significantly outperforms language-dependent stateof-the-art methods in finding the correct split point and that word inflection is a good approximation for compounding morphology.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards Unsupervised and Language-independent Compound Splitting using Inflectional Morphological Transformations

Ziering¹,

Plas²

2016

Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

View full text Add to dashboard Cite

show abstract

“…Other works that used semantic information for compound splitting include Bretschneider and Zillner (2015), who developed a splitting approach relying on a semantic ontology of the medical do-main. They disambiguated candidate splits using semantic relations from the ontology (e.g., Beckenbodenmuskel 'pelvic floor muscle' is binary split to Beckenboden | muskel using the part of relation).…”

Section: Introductionmentioning

confidence: 99%