Assessing the Impact of Incremental Error Detection and Correction. A Case Study on the Italian Universal Dependency Treebank

Chiara Alzetta, Felice Dell’Orletta, Simonetta Montemagni, Maria Simi, Giulia Venturi


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.
Anthology ID:
W18-6001
Volume:
Proceedings of the Second Workshop on Universal Dependencies (UDW 2018)
Month:
November
Year:
2018
Address:
Brussels, Belgium
Venues:
EMNLP | UDW | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–7
Language:
URL:
https://www.aclweb.org/anthology/W18-6001
DOI:
10.18653/v1/W18-6001
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-6001.pdf