@inproceedings{alzetta-etal-2018-assessing,
title = "Assessing the Impact of Incremental Error Detection and Correction. A Case Study on the {I}talian {U}niversal {D}ependency Treebank",
author = "Alzetta, Chiara and
Dell{'}Orletta, Felice and
Montemagni, Simonetta and
Simi, Maria and
Venturi, Giulia",
editor = "de Marneffe, Marie-Catherine and
Lynn, Teresa and
Schuster, Sebastian",
booktitle = "Proceedings of the Second Workshop on Universal Dependencies ({UDW} 2018)",
month = nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6001",
doi = "10.18653/v1/W18-6001",
pages = "1--7",
abstract = "Detection and correction of errors and inconsistencies in {``}gold treebanks{''} are becoming more and more central topics of corpus annotation. The paper illustrates a new incremental method for enhancing treebanks, with particular emphasis on the extension of error patterns across different textual genres and registers. Impact and role of corrections have been assessed in a dependency parsing experiment carried out with four different parsers, whose results are promising. For both evaluation datasets, the performance of parsers increases, in terms of the standard LAS and UAS measures and of a more focused measure taking into account only relations involved in error patterns, and at the level of individual dependencies.",
}
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<abstract>Detection and correction of errors and inconsistencies in “gold treebanks” are becoming more and more central topics of corpus annotation. The paper illustrates a new incremental method for enhancing treebanks, with particular emphasis on the extension of error patterns across different textual genres and registers. Impact and role of corrections have been assessed in a dependency parsing experiment carried out with four different parsers, whose results are promising. For both evaluation datasets, the performance of parsers increases, in terms of the standard LAS and UAS measures and of a more focused measure taking into account only relations involved in error patterns, and at the level of individual dependencies.</abstract>
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%0 Conference Proceedings
%T Assessing the Impact of Incremental Error Detection and Correction. A Case Study on the Italian Universal Dependency Treebank
%A Alzetta, Chiara
%A Dell’Orletta, Felice
%A Montemagni, Simonetta
%A Simi, Maria
%A Venturi, Giulia
%Y de Marneffe, Marie-Catherine
%Y Lynn, Teresa
%Y Schuster, Sebastian
%S Proceedings of the Second Workshop on Universal Dependencies (UDW 2018)
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F alzetta-etal-2018-assessing
%X Detection and correction of errors and inconsistencies in “gold treebanks” are becoming more and more central topics of corpus annotation. The paper illustrates a new incremental method for enhancing treebanks, with particular emphasis on the extension of error patterns across different textual genres and registers. Impact and role of corrections have been assessed in a dependency parsing experiment carried out with four different parsers, whose results are promising. For both evaluation datasets, the performance of parsers increases, in terms of the standard LAS and UAS measures and of a more focused measure taking into account only relations involved in error patterns, and at the level of individual dependencies.
%R 10.18653/v1/W18-6001
%U https://aclanthology.org/W18-6001
%U https://doi.org/10.18653/v1/W18-6001
%P 1-7
Markdown (Informal)
[Assessing the Impact of Incremental Error Detection and Correction. A Case Study on the Italian Universal Dependency Treebank](https://aclanthology.org/W18-6001) (Alzetta et al., UDW 2018)
ACL