LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

Conference Papers

Papers by paper title: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Papers by ID number: 1-50, 51-100, 101-150, 151-200, 201-250, 251-300, 301-350, 351-377.

List of all papers and abstracts.

Previous Paper Next Paper

Title A Parallel Corpus of Italian/German Legal Texts

Authors Gamper Johann (European Academy Bolzano, Scientific Area “Language and Law”, Weggensteinstr. 12a, 39100 Bozen, Italy, jgamper@eurac.edu)

Keywords CES, Corpus Encoding, Parallel Corpus

Session Session WP3 - Multilingual Corpora

Abstract This paper presents the creation of a parallel corpus of Italian and German legal documents which are translations of one another. The corpus, which contains approximately 5 mio. words, is primarily intended as a resource for (semi-)automatic terminology acquisition. The guidelines of the Corpus Encoding Standard have been applied for encoding structural information, segmentation information, and sentence alignment. Since the parallel texts have a one-to-one correspondence on the sentence level, building a perfect sentence alignment is rather straightforward. As a result of this the corpus constitutes also a valuable testbed for the evaluation of alignment algorithms. The paper discusses the intended use of the corpus, the various phases of corpus compilation, and basic statistics.

Title	A Parallel Corpus of Italian/German Legal Texts
Authors	Gamper Johann (European Academy Bolzano, Scientific Area “Language and Law”, Weggensteinstr. 12a, 39100 Bozen, Italy, jgamper@eurac.edu)
Keywords	CES, Corpus Encoding, Parallel Corpus
Session	Session WP3 - Multilingual Corpora
Abstract	This paper presents the creation of a parallel corpus of Italian and German legal documents which are translations of one another. The corpus, which contains approximately 5 mio. words, is primarily intended as a resource for (semi-)automatic terminology acquisition. The guidelines of the Corpus Encoding Standard have been applied for encoding structural information, segmentation information, and sentence alignment. Since the parallel texts have a one-to-one correspondence on the sentence level, building a perfect sentence alignment is rather straightforward. As a result of this the corpus constitutes also a valuable testbed for the evaluation of alignment algorithms. The paper discusses the intended use of the corpus, the various phases of corpus compilation, and basic statistics.