A Document-Level SMT System with Integrated Pronoun Prediction

Christian Hardmeier

doi:10.18653/v1/W15-2510

A Document-Level SMT System with Integrated Pronoun Prediction

Christian Hardmeier

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper describes one of Uppsala University’s submissions to the pronoun-focused machine translation (MT) shared task at DiscoMT 2015. The system is based on phrase-based statistical MT implemented with the document-level decoder Docent. It includes a neural network for pronoun prediction trained with latent anaphora resolution. At translation time, coreference information is obtained from the Stanford CoreNLP system.

Original language	English
Title of host publication	Proceedings of the Second Workshop on Discourse in Machine Translation
Place of Publication	Lisbon, Portugal
Publisher	Association for Computational Linguistics
Pages	72-77
Number of pages	6
ISBN (Electronic)	978-1-941643-32-7
DOIs	https://doi.org/10.18653/v1/W15-2510
Publication status	Published - 21 Sept 2015
Event	Conference on Empirical Methods in Natural Language Processing - Lisbon, Portugal Duration: 17 Sept 2015 → 21 Sept 2015 http://www.emnlp2015.org/

Conference

Conference	Conference on Empirical Methods in Natural Language Processing
Abbreviated title	EMNLP 2015
Country/Territory	Portugal
City	Lisbon
Period	17/09/15 → 21/09/15
Internet address	http://www.emnlp2015.org/

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A Document-level SMT_HARDMEIER_DOA29052015_VOR_CC-BYFinal published version, 113 KBLicence: Creative Commons: Attribution-NonCommercial-ShareAlike (CC BY-NC-SA)

https://www.aclweb.org/anthology/W15-2510Licence: Creative Commons: Attribution-NonCommercial-ShareAlike (CC BY-NC-SA)

Cite this

@inproceedings{b6c51604bc9841c3aa4c2b73cf65bc85,

title = "A Document-Level SMT System with Integrated Pronoun Prediction",

abstract = "This paper describes one of Uppsala University{\textquoteright}s submissions to the pronoun-focused machine translation (MT) shared task at DiscoMT 2015. The system is based on phrase-based statistical MT implemented with the document-level decoder Docent. It includes a neural network for pronoun prediction trained with latent anaphora resolution. At translation time, coreference information is obtained from the Stanford CoreNLP system.",

author = "Christian Hardmeier",

year = "2015",

month = sep,

day = "21",

doi = "10.18653/v1/W15-2510",

language = "English",

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booktitle = "Proceedings of the Second Workshop on Discourse in Machine Translation",

publisher = "Association for Computational Linguistics",

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AB - This paper describes one of Uppsala University’s submissions to the pronoun-focused machine translation (MT) shared task at DiscoMT 2015. The system is based on phrase-based statistical MT implemented with the document-level decoder Docent. It includes a neural network for pronoun prediction trained with latent anaphora resolution. At translation time, coreference information is obtained from the Stanford CoreNLP system.

U2 - 10.18653/v1/W15-2510

DO - 10.18653/v1/W15-2510

M3 - Conference contribution

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EP - 77

BT - Proceedings of the Second Workshop on Discourse in Machine Translation

PB - Association for Computational Linguistics

CY - Lisbon, Portugal

T2 - Conference on Empirical Methods in Natural Language Processing

Y2 - 17 September 2015 through 21 September 2015

ER -

A Document-Level SMT System with Integrated Pronoun Prediction

Abstract

Conference

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