Simple Compound Splitting for German
This paper presents a simple method for German compound splitting that combines a basic frequency-based approach with a form-to-lemma mapping to approximate morphological operations. With the exception of a small set of hand-crafted rules for modeling transitional elements, this approach is resource-poor. In our evaluation, the simple splitter outperforms a splitter relying on rich morphological resources.
Code (0)
등록된 구현이 없습니다.
Tasks
Information RetrievalLEMMAMachine TranslationSimilar Papers 제목 키워드 기반
Chasing the Perfect Splitter: A Comparison of Different Compound Splitting Tools
This paper reports on the evaluation of two compound splitters for German. Compounding is a very frequent phenomenon in German and thus efficient ways of detecting and correctly splitting compound words are needed for na…
Machine TranslationTranslationA Joint Approach to Compound Splitting and Idiomatic Compound Detection
Applications such as machine translation, speech recognition, and information retrieval require efficient handling of noun compounds as they are one of the possible sources for out-of-vocabulary (OOV) words. In-depth pro…
Information RetrievalMachine TranslationRetrievalspeech-recognition+2Analyzing and Aligning German compound nouns
In this paper, we present and evaluate an approach for the compositional alignment of compound nouns using comparable corpora from technical domains. The task of term alignment consists in relating a source language term…
LemmatizationTranslationEvaluating Compound Splitters Extrinsically with Textual Entailment
Traditionally, compound splitters are evaluated intrinsically on gold-standard data or extrinsically on the task of statistical machine translation. We explore a novel way for the extrinsic evaluation of compound splitte…
Information RetrievalMachine TranslationNatural Language InferenceSpeech Recognition+1Splitting Compounds by Semantic Analogy
Compounding is a highly productive word-formation process in some languages that is often problematic for natural language processing applications. In this paper, we investigate whether distributional semantics in the fo…
Machine TranslationTranslationWord Embeddings