Splitting Katakana Noun Compounds by Paraphrasing and Back-transliteration
نویسندگان
چکیده
منابع مشابه
Splitting Noun Compounds via Monolingual and Bilingual Paraphrasing: A Study on Japanese Katakana Words
Word boundaries within noun compounds are not marked by white spaces in a number of languages, unlike in English, and it is beneficial for various NLP applications to split such noun compounds. In the case of Japanese, noun compounds made up of katakana words (i.e., transliterated foreign words) are particularly difficult to split, because katakana words are highly productive and are often outo...
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Automatic transliteration and back-transliteration across languages with drastically different alphabets and phonemes inventories such as English/Korean, English/Japanese, English/Arabic, English/Chinese, etc, have practical importance in machine translation, crosslingual information retrieval, and automatic bilingual dictionary compilation, etc. In this paper, a bi-directional and to some exte...
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Previous research has shown that the meaning of many noun-noun compoundsN1 N2 can be approximated reasonably well by paraphrasing clauses of the form ‘N2 that . . . N1’, where ‘. . . ’ stands for a verb with or without a preposition. For example, malaria mosquito is a ‘mosquito that carries malaria’. Evaluating the quality of such paraphrases is the theme of Task 9 at SemEval-2010. This paper d...
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We present a brief overview of the main challenges in understanding the semantics of noun compounds and consider some known methods. We introduce a new task to be part of SemEval-2010: the interpretation of noun compounds using paraphrasing verbs and prepositions. The task is meant to provide a standard testbed for future research on noun compound semantics. It should also promote paraphrase-ba...
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An important challenge for the automatic analysis of English written text is the abundance of noun compounds: sequences of nouns acting as a single noun. In our view, their semantics is best characterized by the set of all possible paraphrasing verbs, with associated weights, e.g., malaria mosquito is carry (23), spread (16), cause (12), transmit (9), etc. Using Amazon’s Mechanical Turk, we col...
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ژورنال
عنوان ژورنال: Journal of Natural Language Processing
سال: 2014
ISSN: 1340-7619
DOI: 10.5715/jnlp.21.897