Aiding Pronoun Translation with Co-Reference Resolution

By Ronan Le Nagard, Philipp Koehn. 2010

121 citations recorded by the source corpus.

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Citations in the corpus

Context-Aware Neural Machine Translation Learns Anaphora Resolution (2018, background): “Earlier research on this topic focused on handling speciﬁc phenomena, such as translating pro-nouns (Le Nagard and Koehn, 2010; Hardmeier and Federico, 2010; Hardmeier et al., 2015), discourse connectives (Meyer et al., 2012), verb tense (Gong et al., 2012), increasing lexical consistency (Carpuat,…”
Using Coreference Links to Improve Spanish-to-English Machine Translation (2017, background): “For instance, Le Nagard and Koehn (2010) trained an English-French translation model on an annotated corpus in which each occurrence of the English pronouns it and they was annotated with the gender of its antecedent on the target side.”
Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism (2018, background): “A number of approaches have been investigated for DP translation (Le Nagard and Koehn, 2010; Xiang et al., 2013; Wang et al., 2016, 2018).”
Modelling pronominal anaphora in statistical machine translation (2010, background): “This is in contrast with previous research [7], which did not result in any measurable improvement at all.”
Neural Machine Translation with Extended Context (2017, background): “Modest improvements could, for example, be shown for the translation of pronouns (Le Nagard and Koehn, 2010; Hardmeier and Fed-erico, 2010; Hardmeier, 2014) and the generation of appropriate discourse connectives (Meyer et al., 2012).”
Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments (2018, background): “…coreference relates to the issue of translating anaphoric pronouns and is tackled in several works (Guillou, 2016; Hardmeier and Federico, 2010; Le Nagard and Koehn, 2010) and is the central motivation for the DiscoMT shared task on cross-lingual pronoun prediction (Lo´aiciga et al., 2017).”
Pronoun Translation in English-French Machine Translation: An Analysis of Error Types (2018, background): “Gender agreement was long assumed to be the most important problem that needed to be addressed to solve the issue of pronoun translation [1, 30].”