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Are Ellipses Important for Machine Translation?
Abstract This article describes an experiment to evaluate the impact of different types of ellipses discussed in theoretical linguistics on Neural Machine Translation (NMT), using English to Hindi/Telugu as source and target languages.
Why Find the Right One?
The present paper investigates the impact of the anaphoric one words in English on the Neural Machine Translation (NMT) process using English-Hindi as source and target language pair.
Exploring Statistical and Neural Models for Noun Ellipsis Detection and Resolution in English
Computational approaches to noun ellipsis resolution has been sparse, with only a naive rule-based approach that uses syntactic feature constraints for marking noun ellipsis licensors and selecting their antecedents.
Finding The Right One and Resolving it
One-anaphora has figured prominently in theoretical linguistic literature, but computational linguistics research on the phenomenon is sparse.
NoEl: An Annotated Corpus for Noun Ellipsis in English
Ellipsis resolution has been identified as an important step to improve the accuracy of mainstream Natural Language Processing (NLP) tasks such as information retrieval, event extraction, dialog systems, etc.
Using Syntax to Resolve NPE in English
We get an F1-score of 76. 47{\%} for detection and 70. 27{\%} for NPE resolution on the testset.
Automatic Question Generation using Relative Pronouns and Adverbs
This paper presents a system that automatically generates multiple, natural language questions using relative pronouns and relative adverbs from complex English sentences.
