Machine Translation of Spanish Personal and Possessive Pronouns Using Anaphora Probabilities
We implement a fully probabilistic model to combine the hypotheses of a Spanish anaphora resolution system with those of a Spanish-English machine translation system. The probabilities over antecedents are converted into probabilities for the features of translated pronouns, and are integrated with phrase-based MT using an additional translation model for pronouns. The system improves the translation of several Spanish personal and possessive pronouns into English, by solving translation divergencies such as {}ella{'} vs. {}she{'}/{}it{'} or {}su{'} vs. {}his{'}/{}her{'}/{}its{'}/{}their{'}. On a test set with 2,286 pronouns, a baseline system correctly translates 1,055 of them, while ours improves this by 41. Moreover, with oracle antecedents, possessives are translated with an accuracy of 83{\%}.
Code (1)
Tasks
Coreference ResolutionMachine TranslationTranslationSimilar Papers 제목 키워드 기반
Co-reference Resolution of Elided Subjects and Possessive Pronouns in Spanish-English Statistical Machine Translation
This paper presents a straightforward method to integrate co-reference information into phrase-based machine translation to address the problems of i) elided subjects and ii) morphological underspecification of pronouns …
Coreference ResolutionMachine TranslationTranslationMultilingual corpora with coreferential annotation of person entities
This paper presents three corpora with coreferential annotation of person entities for Portuguese, Galician and Spanish. They contain coreference links between several types of pronouns (including elliptical, possessive,…
coreference-resolutionCoreference ResolutionOpen Information ExtractionRelation Extraction+1Italian and Spanish Null Subjects. A Case Study Evaluation in an MT Perspective.
Thanks to their rich morphology, Italian and Spanish allow pro-drop pronouns, i.e., non lexically-realized subject pronouns. Here we distinguish between two different types of null subjects: personal pro-drop and imperso…
ArticlesMachine TranslationTranslationEvaluation Dataset for Zero Pronoun in Japanese to English Translation
In natural language, we often omit some words that are easily understandable from the context. In particular, pronouns of subject, object, and possessive cases are often omitted in Japanese; these are known as zero prono…
Machine TranslationTranslationScalable Cross Lingual Pivots to Model Pronoun Gender for Translation
Machine translation systems with inadequate document understanding can make errors when translating dropped or neutral pronouns into languages with gendered pronouns (e.g., English). Predicting the underlying gender of t…
document understandingMachine TranslationSentenceTranslation