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ParCorFull: a Parallel Corpus Annotated with Full Coreference
Saarland Univ, Saarbrucken, Germany.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.ORCID iD: 0000-0002-6103-7275
Saarland Univ, Saarbrucken, Germany.
2018 (English)In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) / [ed] Nicoletta Calzolari, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis & Takenobu Tokunaga, 2018, p. 423-428Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we describe a parallel corpus annotated with full coreference chains that has been created to address an important problem that machine translation and other multilingual natural language processing (NLP) technologies face - translation of coreference across languages. Recent research in multilingual coreference and automatic pronoun translation has led to important insights into the problem and some promising results. However, its scope has been restricted to pronouns, whereas the phenomenon is not limited to anaphoric pronouns. Our corpus contains parallel texts for the language pair English-German, two major European languages. Despite being typologically very close, these languages still have systemic differences in the realisation of coreference, and thus pose problems for multilingual coreference resolution and machine translation. Our parallel corpus with full annotation of coreference will be a valuable resource with a variety of uses not only for NLP applications, but also for contrastive linguists and researchers in translation studies. This resource supports research on the mechanisms involved in coreference translation in order to develop a better understanding of the phenomenon.

Place, publisher, year, edition, pages
2018. p. 423-428
Keywords [en]
coreference, full coreference, cross-lingual coreference resolution, coreference annotation, linguistic annotation, machine translation, multilingual NLP
National Category
Natural Language Processing
Identifiers
URN: urn:nbn:se:uu:diva-476874ISI: 000725545000065ISBN: 979-10-95546-00-9 (print)OAI: oai:DiVA.org:uu-476874DiVA, id: diva2:1670865
Conference
11th International Conference on Language Resources and Evaluation (LREC), MAY 07-12, 2018, Miyazaki, JAPAN
Funder
Swedish Research Council, 2012-916Swedish Research Council, 2017-930Available from: 2022-06-16 Created: 2022-06-16 Last updated: 2025-02-07Bibliographically approved

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Hardmeier, Christian

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
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Output format
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