Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/102765
Title: Study on the English corresponding unit of Chinese clause
Authors: Feng, W.
Yang, Y.
Li, Y.
Li, X.
Ren, H.
Issue Date: 2016
Publisher: Springer Verlag
Citation: Study on the English corresponding unit of Chinese clause / W. Feng, Y. Yang, Y. Li, et al. — DOI 10.1007/978-3-319-50496-4_11 // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). — 2016. — Vol. 10102. — P. 129-140.
Abstract: This paper annotates the English corresponding units of Chinese clauses in Chinese-English translation and statistically analyzes them. Firstly, based on Chinese clause segmentation, we segment English target text into corresponding units (clause) to get a Chinese-to-English clause-aligned parallel corpus. Then, we annotate the grammatical properties of the English corresponding clauses in the corpus. Finally, we find the distribution characteristics of grammatical properties of English corresponding clauses by statistically analyzing the annotated corpus: There are more clauses (1631,74.41%) than sentences (561,25.59%); there are more major clauses (1719,78.42%) than subordinate clauses (473,21.58%); there are more adverbial clauses (392,82.88%) than attributive clauses (81,17.12%) and more non-defining clauses (358,75.69%) than restrictive relative clauses (115,24.31%) in subordinate clauses; and there are more simple clauses (1142,52.1%) than coordinate clauses (1050,47.9%). © Springer International Publishing AG 2016.
Keywords: CHINESE-TO-ENGLISH TRANSLATION
CLAUSE ALIGNMENT
CLAUSE-BASED
CLAUSES
DISCOURSE-BASED TRANSLATION
PARALLEL CORPUS
COMPUTER SCIENCE
COMPUTERS
LINGUISTICS
NATURAL LANGUAGE PROCESSING SYSTEMS
CLAUSE-BASED
CLAUSES
DISTRIBUTION CHARACTERISTICS
NOCV1
PARALLEL CORPORA
RELATIVE CLAUSE
SUBORDINATE CLAUSE
ARTIFICIAL INTELLIGENCE
TRANSLATION (LANGUAGES)
URI: http://hdl.handle.net/10995/102765
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85003864964
PURE ID: 1381997
1eeb0092-5a69-4d6d-943f-db31eb8a9db9
ISSN: 3029743
DOI: 10.1007/978-3-319-50496-4_11
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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