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Titel: ParCorFull2.0: a Parallel Corpus Annotated with Full Coreference
VerfasserIn: Lapshinova-Koltunski, Ekaterina
Ferreira, Pedro Augusto
Lartaud, Elina
Hardmeier, Christian
Sprache: Englisch
Titel: Proceedings of the Thirteenth Language Resources and Evaluation Conference
Seiten: 805-813
Verlag/Plattform: European Language Resources Association
Erscheinungsjahr: 2022
Erscheinungsort: Marseille, France
Freie Schlagwörter: coreference
entity reference
event reference
cross-lingual coreference resolution
coreference annotation
linguistic annotation
machine translation
multilingual NLP
multilinguality
English
German
French
Portuguese
DDC-Sachgruppe: 400 Sprache, Linguistik
Dokumenttyp: Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag)
Abstract: In this paper, we describe ParCorFull2.0, a parallel corpus annotated with full coreference chains for multiple languages, which is an extension of the existing corpus ParCorFull (Lapshinova-Koltunski et al., 2018). Similar to the previous version, this corpus has been created to address translation of coreference across languages, a phenomenon still challenging for machine translation (MT) and other multilingual natural language processing (NLP) applications. The current version of the corpus that we present here contains not only parallel texts for the language pair English-German, but also for English-French and English-Portuguese, which are all major European languages. The new language pairs belong to the Romance languages. The addition of a new language group creates a need of extension not only in terms of texts added, but also in terms of the annotation guidelines. Both French and Portuguese contain structures not found in English and German. Moreover, Portuguese is a pro-drop language bringing even more systemic differences in the realisation of coreference into our cross-lingual resources. These differences cause 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.
URL der Erstveröffentlichung: https://aclanthology.org/2022.lrec-1.85
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-378908
hdl:20.500.11880/34333
http://dx.doi.org/10.22028/D291-37890
ISBN: 979-10-95546-72-6
Datum des Eintrags: 14-Nov-2022
Drittmittel / Förderung: Christian Hardmeier and Elina Lartaud were supported by the Swedish Research Council under grant 2017-930, which also funded the annotation work of the French data. Pedro Augusto Ferreira was supported by FCT, Foundation for Science and Technology, Portugal, under grant SFRH/BD/146578/2019.
Fakultät: P - Philosophische Fakultät
Fachrichtung: P - Sprachwissenschaft und Sprachtechnologie
Professur: P - Prof. Dr. Elke Teich
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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