Coreference Resolution: Toward End-to-End and Cross-Lingual Systems
The task of coreference resolution has attracted considerable attention in the literature due to its importance in deep language understanding and its potential as a subtask in a variety of complex natural language processing problems. In this study, we outlined the field’s terminology, de...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-01-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/11/2/74 |
id |
doaj-40195e7c6dc9450d8d95bf9c7e0296c2 |
---|---|
record_format |
Article |
spelling |
doaj-40195e7c6dc9450d8d95bf9c7e0296c22020-11-25T02:21:13ZengMDPI AGInformation2078-24892020-01-011127410.3390/info11020074info11020074Coreference Resolution: Toward End-to-End and Cross-Lingual SystemsAndré Ferreira Cruz0Gil Rocha1Henrique Lopes Cardoso2LIACC/DEI, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, PortugalLIACC/DEI, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, PortugalLIACC/DEI, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, PortugalThe task of coreference resolution has attracted considerable attention in the literature due to its importance in deep language understanding and its potential as a subtask in a variety of complex natural language processing problems. In this study, we outlined the field’s terminology, describe existing metrics, their differences and shortcomings, as well as the available corpora and external resources. We analyzed existing state-of-the-art models and approaches, and reviewed recent advances and trends in the field, namely end-to-end systems that jointly model different subtasks of coreference resolution, and cross-lingual systems that aim to overcome the challenges of less-resourced languages. Finally, we discussed the main challenges and open issues faced by coreference resolution systems.https://www.mdpi.com/2078-2489/11/2/74natural language processingcoreference resolutionend-to-end systemscross-language learning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
André Ferreira Cruz Gil Rocha Henrique Lopes Cardoso |
spellingShingle |
André Ferreira Cruz Gil Rocha Henrique Lopes Cardoso Coreference Resolution: Toward End-to-End and Cross-Lingual Systems Information natural language processing coreference resolution end-to-end systems cross-language learning |
author_facet |
André Ferreira Cruz Gil Rocha Henrique Lopes Cardoso |
author_sort |
André Ferreira Cruz |
title |
Coreference Resolution: Toward End-to-End and Cross-Lingual Systems |
title_short |
Coreference Resolution: Toward End-to-End and Cross-Lingual Systems |
title_full |
Coreference Resolution: Toward End-to-End and Cross-Lingual Systems |
title_fullStr |
Coreference Resolution: Toward End-to-End and Cross-Lingual Systems |
title_full_unstemmed |
Coreference Resolution: Toward End-to-End and Cross-Lingual Systems |
title_sort |
coreference resolution: toward end-to-end and cross-lingual systems |
publisher |
MDPI AG |
series |
Information |
issn |
2078-2489 |
publishDate |
2020-01-01 |
description |
The task of coreference resolution has attracted considerable attention in the literature due to its importance in deep language understanding and its potential as a subtask in a variety of complex natural language processing problems. In this study, we outlined the field’s terminology, describe existing metrics, their differences and shortcomings, as well as the available corpora and external resources. We analyzed existing state-of-the-art models and approaches, and reviewed recent advances and trends in the field, namely end-to-end systems that jointly model different subtasks of coreference resolution, and cross-lingual systems that aim to overcome the challenges of less-resourced languages. Finally, we discussed the main challenges and open issues faced by coreference resolution systems. |
topic |
natural language processing coreference resolution end-to-end systems cross-language learning |
url |
https://www.mdpi.com/2078-2489/11/2/74 |
work_keys_str_mv |
AT andreferreiracruz coreferenceresolutiontowardendtoendandcrosslingualsystems AT gilrocha coreferenceresolutiontowardendtoendandcrosslingualsystems AT henriquelopescardoso coreferenceresolutiontowardendtoendandcrosslingualsystems |
_version_ |
1724867716324524032 |