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Modelling Large Parallel Corpora: The Zurich Parallel Corpus Collection


Graën, Johannes; Kew, Tannon; Shaitarova, Anastassia; Volk, Martin (2019). Modelling Large Parallel Corpora: The Zurich Parallel Corpus Collection. In: Challenges in the Management of Large Corpora (CMLC-7), Cardiff, Wales, 22 July 2019 - 22 July 2019.

Abstract

Text corpora come in many different shapes and sizes and carry heterogeneous annotations, depending on their purpose and design. The true benefit of corpora is rooted in their annotation and the method by which this data is encoded is an important factor in their interoperability. We have accumulated a large collection of multilingual and parallel corpora and encoded it in a unified format which is compatible with a broad range of NLP tools and corpus linguistic applications. In this paper, we present our corpus collection and describe a data model and the extensions to the popular CoNLL-U format that enable us to encode it.

Abstract

Text corpora come in many different shapes and sizes and carry heterogeneous annotations, depending on their purpose and design. The true benefit of corpora is rooted in their annotation and the method by which this data is encoded is an important factor in their interoperability. We have accumulated a large collection of multilingual and parallel corpora and encoded it in a unified format which is compatible with a broad range of NLP tools and corpus linguistic applications. In this paper, we present our corpus collection and describe a data model and the extensions to the popular CoNLL-U format that enable us to encode it.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:22 July 2019
Deposited On:04 Oct 2019 13:29
Last Modified:24 Oct 2019 07:30
Publisher:Leibniz-Institut für Deutsche Sprache
OA Status:Green
Publisher DOI:https://doi.org/10.14618/ids-pub-9020
Related URLs:https://ids-pub.bsz-bw.de/frontdoor/index/index/docId/8998 (Publisher)

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