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Found 18 papers, 0 papers with code
Exploiting Cross-Lingual Hints to Discover Event Pronouns
Non-nominal co-reference is much less studied than nominal coreference, partly because of the lack of annotated corpora.
Cross-lingual Incongruences in the Annotation of Coreference
In the present paper, we deal with incongruences in English-German multilingual coreference annotation and present automated methods to discover them.
A Pronoun Test Suite Evaluation of the English--German MT Systems at WMT 2018
We evaluate the output of 16 English-to-German MT systems with respect to the translation of pronouns in the context of the WMT 2018 competition.
Forms of Anaphoric Reference to Organisational Named Entities: Hoping to widen appeal, they diversified
Proper names of organisations are a special case of collective nouns.
Event versus entity co-reference: Effects of context and form of referring expression
Anaphora resolution systems require both an enumeration of possible candidate antecedents and an identification process of the antecedent.
What is it? Disambiguating the different readings of the pronoun `it'
In this paper, we address the problem of predicting one of three functions for the English pronoun {`}it{'}: anaphoric, event reference or pleonastic.
A BiLSTM-based System for Cross-lingual Pronoun Prediction
We describe the Uppsala system for the 2017 DiscoMT shared task on cross-lingual pronoun prediction.
Findings of the 2017 DiscoMT Shared Task on Cross-lingual Pronoun Prediction
We describe the design, the setup, and the evaluation results of the DiscoMT 2017 shared task on cross-lingual pronoun prediction.
Discontinuous Verb Phrases in Parsing and Machine Translation of English and German
In this paper, we focus on the verb-particle (V-Prt) split construction in English and German and its difficulty for parsing and Machine Translation (MT).
English-French Verb Phrase Alignment in Europarl for Tense Translation Modeling
This paper presents a method for verb phrase (VP) alignment in an English-French parallel corpus and its use for improving statistical machine translation (SMT) of verb tenses.
Italian 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.
