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Cross-Linguistic Annotation of Narrativity for English/French Verb Tense Disambiguation

Publikationsart Peer-reviewed
Publikationsform Tagungsbeitrag (peer-reviewed)
Autor/in Cristina Grisot and Thomas Meyer,
Projekt MODERN: Modeling discourse entities and relations for coherent machine translation
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Tagungsbeitrag (peer-reviewed)

Titel der Proceedings Proceedings of LREC 2014
Ort Reykjavik

Open Access


This paper presents manual and automatic annotation experiments for a pragmatic verb tense feature (narrativity) in English/French parallel corpora. The feature is considered to play an important role for translating English Simple Past tense into French, where three different tenses are available. Whether the French Pass´e Compos´e, Pass´e Simple or Imparfait should be used is highly dependent on a longer-range context, in which either narrative events ordered in time or mere non-narrative state of affairs in the past are described. This longer-range context is usually not available to current machine translation (MT) systems, that are trained on parallel corpora. Annotating narrativity prior to translation is therefore likely to help current MT systems. Our experiments show that narrativity can be reliably identified with kappa-values of up to 0.91 in manual annotation and with F1 scores of up to 0.72 in automatic annotation.